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You searched for subject:(Cancer classification). Showing records 1 – 30 of 265 total matches.

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Duquesne University

1. Chen, Pu. Classification Tree Models for Predicting Cancer Status.

Degree: MS, Computational Mathematics, 2009, Duquesne University

 Early detection of cancers might improve the clinical outcomes. Multiple biomarkers with a novel LabMAP technology were used as the laboratory method to develop the… (more)

Subjects/Keywords: classification tree; cancer

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APA (6th Edition):

Chen, P. (2009). Classification Tree Models for Predicting Cancer Status. (Masters Thesis). Duquesne University. Retrieved from https://dsc.duq.edu/etd/397

Chicago Manual of Style (16th Edition):

Chen, Pu. “Classification Tree Models for Predicting Cancer Status.” 2009. Masters Thesis, Duquesne University. Accessed February 21, 2020. https://dsc.duq.edu/etd/397.

MLA Handbook (7th Edition):

Chen, Pu. “Classification Tree Models for Predicting Cancer Status.” 2009. Web. 21 Feb 2020.

Vancouver:

Chen P. Classification Tree Models for Predicting Cancer Status. [Internet] [Masters thesis]. Duquesne University; 2009. [cited 2020 Feb 21]. Available from: https://dsc.duq.edu/etd/397.

Council of Science Editors:

Chen P. Classification Tree Models for Predicting Cancer Status. [Masters Thesis]. Duquesne University; 2009. Available from: https://dsc.duq.edu/etd/397


Louisiana State University

2. Duncan, William Evans. Gene set based ensemble methods for cancer classification.

Degree: PhD, Computer Sciences, 2013, Louisiana State University

 Diagnosis of cancer very often depends on conclusions drawn after both clinical and microscopic examinations of tissues to study the manifestation of the disease in… (more)

Subjects/Keywords: Ensemble classification gene set cancer

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APA (6th Edition):

Duncan, W. E. (2013). Gene set based ensemble methods for cancer classification. (Doctoral Dissertation). Louisiana State University. Retrieved from etd-05272013-105338 ; https://digitalcommons.lsu.edu/gradschool_dissertations/3118

Chicago Manual of Style (16th Edition):

Duncan, William Evans. “Gene set based ensemble methods for cancer classification.” 2013. Doctoral Dissertation, Louisiana State University. Accessed February 21, 2020. etd-05272013-105338 ; https://digitalcommons.lsu.edu/gradschool_dissertations/3118.

MLA Handbook (7th Edition):

Duncan, William Evans. “Gene set based ensemble methods for cancer classification.” 2013. Web. 21 Feb 2020.

Vancouver:

Duncan WE. Gene set based ensemble methods for cancer classification. [Internet] [Doctoral dissertation]. Louisiana State University; 2013. [cited 2020 Feb 21]. Available from: etd-05272013-105338 ; https://digitalcommons.lsu.edu/gradschool_dissertations/3118.

Council of Science Editors:

Duncan WE. Gene set based ensemble methods for cancer classification. [Doctoral Dissertation]. Louisiana State University; 2013. Available from: etd-05272013-105338 ; https://digitalcommons.lsu.edu/gradschool_dissertations/3118


IUPUI

3. Pawar, Aniruddha. CLASSIFICATION OF BREAST CANCER CELL LINES INTO SUBTYPES BASED ON GENETIC PROFILES.

Degree: 2015, IUPUI

Indiana University-Purdue University Indianapolis (IUPUI)

Today we know that there are several different types of breast cancer. Accurate identification breast cancer subtype is extremely important… (more)

Subjects/Keywords: Breast cancer; Cell lines; Classification

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APA (6th Edition):

Pawar, A. (2015). CLASSIFICATION OF BREAST CANCER CELL LINES INTO SUBTYPES BASED ON GENETIC PROFILES. (Thesis). IUPUI. Retrieved from http://hdl.handle.net/1805/7912

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Pawar, Aniruddha. “CLASSIFICATION OF BREAST CANCER CELL LINES INTO SUBTYPES BASED ON GENETIC PROFILES.” 2015. Thesis, IUPUI. Accessed February 21, 2020. http://hdl.handle.net/1805/7912.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Pawar, Aniruddha. “CLASSIFICATION OF BREAST CANCER CELL LINES INTO SUBTYPES BASED ON GENETIC PROFILES.” 2015. Web. 21 Feb 2020.

Vancouver:

Pawar A. CLASSIFICATION OF BREAST CANCER CELL LINES INTO SUBTYPES BASED ON GENETIC PROFILES. [Internet] [Thesis]. IUPUI; 2015. [cited 2020 Feb 21]. Available from: http://hdl.handle.net/1805/7912.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Pawar A. CLASSIFICATION OF BREAST CANCER CELL LINES INTO SUBTYPES BASED ON GENETIC PROFILES. [Thesis]. IUPUI; 2015. Available from: http://hdl.handle.net/1805/7912

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

4. Jing, Lun. Mécanismes moléculaires de la régulation thyroïdienne par l’iode : recherche des protéines iodées et application de la métabolomique aux études des pathologies de la thyroïde et d’autres organes : Identification of an iodinated protein involved in thyroid regulation by iodide and metabolomics approach in the study of thyroid disruptors and cancers.

Degree: Docteur es, Interactions moléculaires et cellulaires, 2018, Côte d'Azur

 La thyroïde est une glande endocrine importante pour le contrôle du métabolisme, le développement et la croissance des mammifères. Sa fonction est stimulée par la… (more)

Subjects/Keywords: Thyroïde; Iodation; Peroxyrédoxine; Métabolomique; Cancer; Classification; Thyroid; Iodination; Peroxiredoxin; Metabolomics; Cancer; Classification

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APA (6th Edition):

Jing, L. (2018). Mécanismes moléculaires de la régulation thyroïdienne par l’iode : recherche des protéines iodées et application de la métabolomique aux études des pathologies de la thyroïde et d’autres organes : Identification of an iodinated protein involved in thyroid regulation by iodide and metabolomics approach in the study of thyroid disruptors and cancers. (Doctoral Dissertation). Côte d'Azur. Retrieved from http://www.theses.fr/2018AZUR4048

Chicago Manual of Style (16th Edition):

Jing, Lun. “Mécanismes moléculaires de la régulation thyroïdienne par l’iode : recherche des protéines iodées et application de la métabolomique aux études des pathologies de la thyroïde et d’autres organes : Identification of an iodinated protein involved in thyroid regulation by iodide and metabolomics approach in the study of thyroid disruptors and cancers.” 2018. Doctoral Dissertation, Côte d'Azur. Accessed February 21, 2020. http://www.theses.fr/2018AZUR4048.

MLA Handbook (7th Edition):

Jing, Lun. “Mécanismes moléculaires de la régulation thyroïdienne par l’iode : recherche des protéines iodées et application de la métabolomique aux études des pathologies de la thyroïde et d’autres organes : Identification of an iodinated protein involved in thyroid regulation by iodide and metabolomics approach in the study of thyroid disruptors and cancers.” 2018. Web. 21 Feb 2020.

Vancouver:

Jing L. Mécanismes moléculaires de la régulation thyroïdienne par l’iode : recherche des protéines iodées et application de la métabolomique aux études des pathologies de la thyroïde et d’autres organes : Identification of an iodinated protein involved in thyroid regulation by iodide and metabolomics approach in the study of thyroid disruptors and cancers. [Internet] [Doctoral dissertation]. Côte d'Azur; 2018. [cited 2020 Feb 21]. Available from: http://www.theses.fr/2018AZUR4048.

Council of Science Editors:

Jing L. Mécanismes moléculaires de la régulation thyroïdienne par l’iode : recherche des protéines iodées et application de la métabolomique aux études des pathologies de la thyroïde et d’autres organes : Identification of an iodinated protein involved in thyroid regulation by iodide and metabolomics approach in the study of thyroid disruptors and cancers. [Doctoral Dissertation]. Côte d'Azur; 2018. Available from: http://www.theses.fr/2018AZUR4048


University of Manitoba

5. Feizi, Nikta. Computational prediction of the pathogenic status of cancer-specific somatic variants.

Degree: Biochemistry and Medical Genetics, 2019, University of Manitoba

 Background: In-silico classification of the pathogenic status of the ever-increasing somatic variants, identified through cancer genomic sequencing, is shown to be promising in promoting the… (more)

Subjects/Keywords: Cancer somatic variants; computational classification; breast cancer; MUC16; TP53

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APA (6th Edition):

Feizi, N. (2019). Computational prediction of the pathogenic status of cancer-specific somatic variants. (Masters Thesis). University of Manitoba. Retrieved from http://hdl.handle.net/1993/34081

Chicago Manual of Style (16th Edition):

Feizi, Nikta. “Computational prediction of the pathogenic status of cancer-specific somatic variants.” 2019. Masters Thesis, University of Manitoba. Accessed February 21, 2020. http://hdl.handle.net/1993/34081.

MLA Handbook (7th Edition):

Feizi, Nikta. “Computational prediction of the pathogenic status of cancer-specific somatic variants.” 2019. Web. 21 Feb 2020.

Vancouver:

Feizi N. Computational prediction of the pathogenic status of cancer-specific somatic variants. [Internet] [Masters thesis]. University of Manitoba; 2019. [cited 2020 Feb 21]. Available from: http://hdl.handle.net/1993/34081.

Council of Science Editors:

Feizi N. Computational prediction of the pathogenic status of cancer-specific somatic variants. [Masters Thesis]. University of Manitoba; 2019. Available from: http://hdl.handle.net/1993/34081

6. Garcia, Maxime. Découverte de biomarqueurs prédictifs en cancer du sein par intégration transcriptome-interactome : Biomarkers discovery in breast cancer by Interactome-Transcriptome Integration.

Degree: Docteur es, Génomique et bioinformatique, 2013, Aix Marseille Université

L’arrivée des technologies à haut-débit pour mesurer l’expression des gènes a permis l’utilisation de signatures génomiques pour prédire des conditions cliniques ou la survie du… (more)

Subjects/Keywords: Transcriptome; Interactome; Intégration de données; Signature; Biomarqueurs; Cancer; Cancer du Sein; Réseaux de gène; Classification; SVM; Transcriptome; Interactome; Data Integration; Signature; Biomarkers; Cancer; Breast Cancer; Gene Networks; Classification; SVM; 570

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APA (6th Edition):

Garcia, M. (2013). Découverte de biomarqueurs prédictifs en cancer du sein par intégration transcriptome-interactome : Biomarkers discovery in breast cancer by Interactome-Transcriptome Integration. (Doctoral Dissertation). Aix Marseille Université. Retrieved from http://www.theses.fr/2013AIXM4109

Chicago Manual of Style (16th Edition):

Garcia, Maxime. “Découverte de biomarqueurs prédictifs en cancer du sein par intégration transcriptome-interactome : Biomarkers discovery in breast cancer by Interactome-Transcriptome Integration.” 2013. Doctoral Dissertation, Aix Marseille Université. Accessed February 21, 2020. http://www.theses.fr/2013AIXM4109.

MLA Handbook (7th Edition):

Garcia, Maxime. “Découverte de biomarqueurs prédictifs en cancer du sein par intégration transcriptome-interactome : Biomarkers discovery in breast cancer by Interactome-Transcriptome Integration.” 2013. Web. 21 Feb 2020.

Vancouver:

Garcia M. Découverte de biomarqueurs prédictifs en cancer du sein par intégration transcriptome-interactome : Biomarkers discovery in breast cancer by Interactome-Transcriptome Integration. [Internet] [Doctoral dissertation]. Aix Marseille Université 2013. [cited 2020 Feb 21]. Available from: http://www.theses.fr/2013AIXM4109.

Council of Science Editors:

Garcia M. Découverte de biomarqueurs prédictifs en cancer du sein par intégration transcriptome-interactome : Biomarkers discovery in breast cancer by Interactome-Transcriptome Integration. [Doctoral Dissertation]. Aix Marseille Université 2013. Available from: http://www.theses.fr/2013AIXM4109

7. Marisa, Laetitia. Classification et caractérisation des cancers colorectaux par approches omiques : Classification and characterization of colorectal cancer by omics approaches.

Degree: Docteur es, Génomique, Cancérologie, Médecine, Santé, 2015, Université Pierre et Marie Curie – Paris VI

Le cancer du côlon (CC) est l'un des cancers les plus fréquents et les plus mortels en France et dans le monde. Près de la… (more)

Subjects/Keywords: Cancer; Côlon; Classification; Génomique; Sous-Types; Médecine personnalisée; Pronostic; Cancer; Colon; Genomic; 576

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APA (6th Edition):

Marisa, L. (2015). Classification et caractérisation des cancers colorectaux par approches omiques : Classification and characterization of colorectal cancer by omics approaches. (Doctoral Dissertation). Université Pierre et Marie Curie – Paris VI. Retrieved from http://www.theses.fr/2015PA066235

Chicago Manual of Style (16th Edition):

Marisa, Laetitia. “Classification et caractérisation des cancers colorectaux par approches omiques : Classification and characterization of colorectal cancer by omics approaches.” 2015. Doctoral Dissertation, Université Pierre et Marie Curie – Paris VI. Accessed February 21, 2020. http://www.theses.fr/2015PA066235.

MLA Handbook (7th Edition):

Marisa, Laetitia. “Classification et caractérisation des cancers colorectaux par approches omiques : Classification and characterization of colorectal cancer by omics approaches.” 2015. Web. 21 Feb 2020.

Vancouver:

Marisa L. Classification et caractérisation des cancers colorectaux par approches omiques : Classification and characterization of colorectal cancer by omics approaches. [Internet] [Doctoral dissertation]. Université Pierre et Marie Curie – Paris VI; 2015. [cited 2020 Feb 21]. Available from: http://www.theses.fr/2015PA066235.

Council of Science Editors:

Marisa L. Classification et caractérisation des cancers colorectaux par approches omiques : Classification and characterization of colorectal cancer by omics approaches. [Doctoral Dissertation]. Université Pierre et Marie Curie – Paris VI; 2015. Available from: http://www.theses.fr/2015PA066235


University of New Orleans

8. Coco, Joseph. PARSES: A Pipeline for Analysis of RNA-Sequencing Exogenous Sequences.

Degree: MS, Computer Science, 2011, University of New Orleans

 RNA-Sequencing (RNA-Seq) has become one of the most widely used techniques to interrogate the transcriptome of an organism since the advent of next generation sequencing… (more)

Subjects/Keywords: exogenous agents; RNA-Seq; contamination; sequence alignment; cancer etiology; sequence assembly; taxonomical classification; cancer treatment

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APA (6th Edition):

Coco, J. (2011). PARSES: A Pipeline for Analysis of RNA-Sequencing Exogenous Sequences. (Thesis). University of New Orleans. Retrieved from https://scholarworks.uno.edu/td/1297

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Coco, Joseph. “PARSES: A Pipeline for Analysis of RNA-Sequencing Exogenous Sequences.” 2011. Thesis, University of New Orleans. Accessed February 21, 2020. https://scholarworks.uno.edu/td/1297.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Coco, Joseph. “PARSES: A Pipeline for Analysis of RNA-Sequencing Exogenous Sequences.” 2011. Web. 21 Feb 2020.

Vancouver:

Coco J. PARSES: A Pipeline for Analysis of RNA-Sequencing Exogenous Sequences. [Internet] [Thesis]. University of New Orleans; 2011. [cited 2020 Feb 21]. Available from: https://scholarworks.uno.edu/td/1297.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Coco J. PARSES: A Pipeline for Analysis of RNA-Sequencing Exogenous Sequences. [Thesis]. University of New Orleans; 2011. Available from: https://scholarworks.uno.edu/td/1297

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Adelaide

9. Winderbaum, Lyron Juan. Statistical Treatment of Proteomic Imaging Mass Spectrometry Data.

Degree: 2016, University of Adelaide

 Proteomic imaging mass spectrometry is an emerging field, and produces large amounts of high-dimensional data. We propose approaches to extracting useful information from these data… (more)

Subjects/Keywords: Bioinformatics; clustering; classification; proteomics; mass spectrometry imaging; MALDI; ovarian cancer; endometrial cancer

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APA (6th Edition):

Winderbaum, L. J. (2016). Statistical Treatment of Proteomic Imaging Mass Spectrometry Data. (Thesis). University of Adelaide. Retrieved from http://hdl.handle.net/2440/119709

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Winderbaum, Lyron Juan. “Statistical Treatment of Proteomic Imaging Mass Spectrometry Data.” 2016. Thesis, University of Adelaide. Accessed February 21, 2020. http://hdl.handle.net/2440/119709.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Winderbaum, Lyron Juan. “Statistical Treatment of Proteomic Imaging Mass Spectrometry Data.” 2016. Web. 21 Feb 2020.

Vancouver:

Winderbaum LJ. Statistical Treatment of Proteomic Imaging Mass Spectrometry Data. [Internet] [Thesis]. University of Adelaide; 2016. [cited 2020 Feb 21]. Available from: http://hdl.handle.net/2440/119709.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Winderbaum LJ. Statistical Treatment of Proteomic Imaging Mass Spectrometry Data. [Thesis]. University of Adelaide; 2016. Available from: http://hdl.handle.net/2440/119709

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

10. Prestat, Emmanuel. Les réseaux bayésiens : classification et recherche de réseaux locaux en cancérologie : Classification and capture of regulation networks with bayesian networks in oncology.

Degree: Docteur es, Bioinformatique, 2010, Université Claude Bernard – Lyon I

En cancérologie, les puces à ADN mesurant le transcriptome sont devenues un outil commun pour chercher à caractériser plus finement les pathologies, dans l’espoir de… (more)

Subjects/Keywords: Réseaux cellulaires; Transcriptome; Réseaux Bayésiens; Classification; Sélection de variables; Cancer; Cellular networks; Transcriptome; Bayesian Networks; Classification; Gene selection; Cancer

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APA (6th Edition):

Prestat, E. (2010). Les réseaux bayésiens : classification et recherche de réseaux locaux en cancérologie : Classification and capture of regulation networks with bayesian networks in oncology. (Doctoral Dissertation). Université Claude Bernard – Lyon I. Retrieved from http://www.theses.fr/2010LYO10065

Chicago Manual of Style (16th Edition):

Prestat, Emmanuel. “Les réseaux bayésiens : classification et recherche de réseaux locaux en cancérologie : Classification and capture of regulation networks with bayesian networks in oncology.” 2010. Doctoral Dissertation, Université Claude Bernard – Lyon I. Accessed February 21, 2020. http://www.theses.fr/2010LYO10065.

MLA Handbook (7th Edition):

Prestat, Emmanuel. “Les réseaux bayésiens : classification et recherche de réseaux locaux en cancérologie : Classification and capture of regulation networks with bayesian networks in oncology.” 2010. Web. 21 Feb 2020.

Vancouver:

Prestat E. Les réseaux bayésiens : classification et recherche de réseaux locaux en cancérologie : Classification and capture of regulation networks with bayesian networks in oncology. [Internet] [Doctoral dissertation]. Université Claude Bernard – Lyon I; 2010. [cited 2020 Feb 21]. Available from: http://www.theses.fr/2010LYO10065.

Council of Science Editors:

Prestat E. Les réseaux bayésiens : classification et recherche de réseaux locaux en cancérologie : Classification and capture of regulation networks with bayesian networks in oncology. [Doctoral Dissertation]. Université Claude Bernard – Lyon I; 2010. Available from: http://www.theses.fr/2010LYO10065

11. Heo, Tae Keun. Breast Cancer Classification of Mammographic Masses Using Circularity Max Metric, A New Method.

Degree: MS, Electrical Engineering and Computer Science, 2016, South Dakota State University

  Breast cancer classification can be divided into two categories. The first category is a benign tumor, and the other is a malignant tumor. The… (more)

Subjects/Keywords: Breast cancer; classification; MRI; Biomedical; Computer Engineering; Computer Sciences

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APA (6th Edition):

Heo, T. K. (2016). Breast Cancer Classification of Mammographic Masses Using Circularity Max Metric, A New Method. (Masters Thesis). South Dakota State University. Retrieved from http://openprairie.sdstate.edu/etd/1113

Chicago Manual of Style (16th Edition):

Heo, Tae Keun. “Breast Cancer Classification of Mammographic Masses Using Circularity Max Metric, A New Method.” 2016. Masters Thesis, South Dakota State University. Accessed February 21, 2020. http://openprairie.sdstate.edu/etd/1113.

MLA Handbook (7th Edition):

Heo, Tae Keun. “Breast Cancer Classification of Mammographic Masses Using Circularity Max Metric, A New Method.” 2016. Web. 21 Feb 2020.

Vancouver:

Heo TK. Breast Cancer Classification of Mammographic Masses Using Circularity Max Metric, A New Method. [Internet] [Masters thesis]. South Dakota State University; 2016. [cited 2020 Feb 21]. Available from: http://openprairie.sdstate.edu/etd/1113.

Council of Science Editors:

Heo TK. Breast Cancer Classification of Mammographic Masses Using Circularity Max Metric, A New Method. [Masters Thesis]. South Dakota State University; 2016. Available from: http://openprairie.sdstate.edu/etd/1113


University of Akron

12. Jose, Adarsh. Gene Selection by 1-D Discrete Wavelet Transform for Classifying Cancer Samples Using DNA Microarray Date.

Degree: MSin Engineering, Biomedical Engineering, 2009, University of Akron

  Selecting a set of highly discriminant genes for biological samples is an important task for designing highly efficient classifiers using DNA microarray data. The… (more)

Subjects/Keywords: Biomedical Research; discrete wavelet transform; microarray data; cancer; gene selection; classification

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APA (6th Edition):

Jose, A. (2009). Gene Selection by 1-D Discrete Wavelet Transform for Classifying Cancer Samples Using DNA Microarray Date. (Masters Thesis). University of Akron. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=akron1240851642

Chicago Manual of Style (16th Edition):

Jose, Adarsh. “Gene Selection by 1-D Discrete Wavelet Transform for Classifying Cancer Samples Using DNA Microarray Date.” 2009. Masters Thesis, University of Akron. Accessed February 21, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=akron1240851642.

MLA Handbook (7th Edition):

Jose, Adarsh. “Gene Selection by 1-D Discrete Wavelet Transform for Classifying Cancer Samples Using DNA Microarray Date.” 2009. Web. 21 Feb 2020.

Vancouver:

Jose A. Gene Selection by 1-D Discrete Wavelet Transform for Classifying Cancer Samples Using DNA Microarray Date. [Internet] [Masters thesis]. University of Akron; 2009. [cited 2020 Feb 21]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=akron1240851642.

Council of Science Editors:

Jose A. Gene Selection by 1-D Discrete Wavelet Transform for Classifying Cancer Samples Using DNA Microarray Date. [Masters Thesis]. University of Akron; 2009. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=akron1240851642


Universiteit Utrecht

13. Hooff, S.R. van. Patient stratification using global gene expression signatures.

Degree: 2015, Universiteit Utrecht

 This thesis describes three different studies that have used gene expression profiling to distinguish different disease phenotypes. The first study involves the transition of a… (more)

Subjects/Keywords: gene expresssion; patient classification; microarray; cancer; IVF; RIF

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APA (6th Edition):

Hooff, S. R. v. (2015). Patient stratification using global gene expression signatures. (Doctoral Dissertation). Universiteit Utrecht. Retrieved from http://dspace.library.uu.nl:8080/handle/1874/309218

Chicago Manual of Style (16th Edition):

Hooff, S R van. “Patient stratification using global gene expression signatures.” 2015. Doctoral Dissertation, Universiteit Utrecht. Accessed February 21, 2020. http://dspace.library.uu.nl:8080/handle/1874/309218.

MLA Handbook (7th Edition):

Hooff, S R van. “Patient stratification using global gene expression signatures.” 2015. Web. 21 Feb 2020.

Vancouver:

Hooff SRv. Patient stratification using global gene expression signatures. [Internet] [Doctoral dissertation]. Universiteit Utrecht; 2015. [cited 2020 Feb 21]. Available from: http://dspace.library.uu.nl:8080/handle/1874/309218.

Council of Science Editors:

Hooff SRv. Patient stratification using global gene expression signatures. [Doctoral Dissertation]. Universiteit Utrecht; 2015. Available from: http://dspace.library.uu.nl:8080/handle/1874/309218

14. Itoh, Takahiro; Saito, Miho; Marugami, Nagaaki; Hirai, Toshiko; Marugami, Aki; Takahama, Junko; Tanaka, Toshihiro. Correlation between the ABC classification and radiological findings for assessing gastric cancer risk. : 胃がんリスク評価におけるABC分類とX線所見の関連性について.

Degree: 博士(医学), 2015, Nara Medical University / 奈良県立医科大学

PURPOSE:To investigate the correlation between ABC risk assessment and radiological findings of gastric mucosa and to propose an improved method for gastric cancer screening.MATERIALS AND… (more)

Subjects/Keywords: Helicobacter pylori; ABC classification; Gastric cancer; Radiological finding

Page 1

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APA (6th Edition):

Itoh, Takahiro; Saito, Miho; Marugami, Nagaaki; Hirai, Toshiko; Marugami, Aki; Takahama, Junko; Tanaka, T. (2015). Correlation between the ABC classification and radiological findings for assessing gastric cancer risk. : 胃がんリスク評価におけるABC分類とX線所見の関連性について. (Thesis). Nara Medical University / 奈良県立医科大学. Retrieved from http://hdl.handle.net/10564/3108

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Itoh, Takahiro; Saito, Miho; Marugami, Nagaaki; Hirai, Toshiko; Marugami, Aki; Takahama, Junko; Tanaka, Toshihiro. “Correlation between the ABC classification and radiological findings for assessing gastric cancer risk. : 胃がんリスク評価におけるABC分類とX線所見の関連性について.” 2015. Thesis, Nara Medical University / 奈良県立医科大学. Accessed February 21, 2020. http://hdl.handle.net/10564/3108.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Itoh, Takahiro; Saito, Miho; Marugami, Nagaaki; Hirai, Toshiko; Marugami, Aki; Takahama, Junko; Tanaka, Toshihiro. “Correlation between the ABC classification and radiological findings for assessing gastric cancer risk. : 胃がんリスク評価におけるABC分類とX線所見の関連性について.” 2015. Web. 21 Feb 2020.

Vancouver:

Itoh, Takahiro; Saito, Miho; Marugami, Nagaaki; Hirai, Toshiko; Marugami, Aki; Takahama, Junko; Tanaka T. Correlation between the ABC classification and radiological findings for assessing gastric cancer risk. : 胃がんリスク評価におけるABC分類とX線所見の関連性について. [Internet] [Thesis]. Nara Medical University / 奈良県立医科大学; 2015. [cited 2020 Feb 21]. Available from: http://hdl.handle.net/10564/3108.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Itoh, Takahiro; Saito, Miho; Marugami, Nagaaki; Hirai, Toshiko; Marugami, Aki; Takahama, Junko; Tanaka T. Correlation between the ABC classification and radiological findings for assessing gastric cancer risk. : 胃がんリスク評価におけるABC分類とX線所見の関連性について. [Thesis]. Nara Medical University / 奈良県立医科大学; 2015. Available from: http://hdl.handle.net/10564/3108

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Delft University of Technology

15. Lai, C. Supervised classification and spatial dependency analysis in human cancer using high throughput data.

Degree: 2008, Delft University of Technology

Subjects/Keywords: classification; expression data; cancer research

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Lai, C. (2008). Supervised classification and spatial dependency analysis in human cancer using high throughput data. (Doctoral Dissertation). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:1eae37b1-bcaf-4213-b74d-ef7e4395d9e4 ; urn:NBN:nl:ui:24-uuid:1eae37b1-bcaf-4213-b74d-ef7e4395d9e4 ; urn:NBN:nl:ui:24-uuid:1eae37b1-bcaf-4213-b74d-ef7e4395d9e4 ; http://resolver.tudelft.nl/uuid:1eae37b1-bcaf-4213-b74d-ef7e4395d9e4

Chicago Manual of Style (16th Edition):

Lai, C. “Supervised classification and spatial dependency analysis in human cancer using high throughput data.” 2008. Doctoral Dissertation, Delft University of Technology. Accessed February 21, 2020. http://resolver.tudelft.nl/uuid:1eae37b1-bcaf-4213-b74d-ef7e4395d9e4 ; urn:NBN:nl:ui:24-uuid:1eae37b1-bcaf-4213-b74d-ef7e4395d9e4 ; urn:NBN:nl:ui:24-uuid:1eae37b1-bcaf-4213-b74d-ef7e4395d9e4 ; http://resolver.tudelft.nl/uuid:1eae37b1-bcaf-4213-b74d-ef7e4395d9e4.

MLA Handbook (7th Edition):

Lai, C. “Supervised classification and spatial dependency analysis in human cancer using high throughput data.” 2008. Web. 21 Feb 2020.

Vancouver:

Lai C. Supervised classification and spatial dependency analysis in human cancer using high throughput data. [Internet] [Doctoral dissertation]. Delft University of Technology; 2008. [cited 2020 Feb 21]. Available from: http://resolver.tudelft.nl/uuid:1eae37b1-bcaf-4213-b74d-ef7e4395d9e4 ; urn:NBN:nl:ui:24-uuid:1eae37b1-bcaf-4213-b74d-ef7e4395d9e4 ; urn:NBN:nl:ui:24-uuid:1eae37b1-bcaf-4213-b74d-ef7e4395d9e4 ; http://resolver.tudelft.nl/uuid:1eae37b1-bcaf-4213-b74d-ef7e4395d9e4.

Council of Science Editors:

Lai C. Supervised classification and spatial dependency analysis in human cancer using high throughput data. [Doctoral Dissertation]. Delft University of Technology; 2008. Available from: http://resolver.tudelft.nl/uuid:1eae37b1-bcaf-4213-b74d-ef7e4395d9e4 ; urn:NBN:nl:ui:24-uuid:1eae37b1-bcaf-4213-b74d-ef7e4395d9e4 ; urn:NBN:nl:ui:24-uuid:1eae37b1-bcaf-4213-b74d-ef7e4395d9e4 ; http://resolver.tudelft.nl/uuid:1eae37b1-bcaf-4213-b74d-ef7e4395d9e4


University of South Florida

16. Geiger, Benjamin. Change Descriptors for Determining Nodule Malignancy in Lung CT Screening Images.

Degree: 2018, University of South Florida

 Computed tomography (CT) imagery is an important weapon in the fight against lung cancer; various forms of lung cancer are routinely diagnosed from CT imagery.… (more)

Subjects/Keywords: Classification; Computer-Aided Diagnosis; Lung Cancer; Prognosis; Radiomics; Computer Sciences

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Geiger, B. (2018). Change Descriptors for Determining Nodule Malignancy in Lung CT Screening Images. (Thesis). University of South Florida. Retrieved from https://scholarcommons.usf.edu/etd/7505

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Geiger, Benjamin. “Change Descriptors for Determining Nodule Malignancy in Lung CT Screening Images.” 2018. Thesis, University of South Florida. Accessed February 21, 2020. https://scholarcommons.usf.edu/etd/7505.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Geiger, Benjamin. “Change Descriptors for Determining Nodule Malignancy in Lung CT Screening Images.” 2018. Web. 21 Feb 2020.

Vancouver:

Geiger B. Change Descriptors for Determining Nodule Malignancy in Lung CT Screening Images. [Internet] [Thesis]. University of South Florida; 2018. [cited 2020 Feb 21]. Available from: https://scholarcommons.usf.edu/etd/7505.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Geiger B. Change Descriptors for Determining Nodule Malignancy in Lung CT Screening Images. [Thesis]. University of South Florida; 2018. Available from: https://scholarcommons.usf.edu/etd/7505

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

17. Aminikhanghahi, Samaneh. FGMM-based Computer Aided Diagnosis to Classify Benign/Malignant Breast Mammogram Images.

Degree: MS, Electrical Engineering and Computer Science, 2014, South Dakota State University

  Mammography is potentially a convenient screening method to be comfortable and effective in early detection of breast cancer, but its interpretation is difficult due… (more)

Subjects/Keywords: Breast Cancer; CAD; Feature extraction; Classification; SVM; GMM; FLS; FGMM; MCC

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APA (6th Edition):

Aminikhanghahi, S. (2014). FGMM-based Computer Aided Diagnosis to Classify Benign/Malignant Breast Mammogram Images. (Masters Thesis). South Dakota State University. Retrieved from https://openprairie.sdstate.edu/etd/2074

Chicago Manual of Style (16th Edition):

Aminikhanghahi, Samaneh. “FGMM-based Computer Aided Diagnosis to Classify Benign/Malignant Breast Mammogram Images.” 2014. Masters Thesis, South Dakota State University. Accessed February 21, 2020. https://openprairie.sdstate.edu/etd/2074.

MLA Handbook (7th Edition):

Aminikhanghahi, Samaneh. “FGMM-based Computer Aided Diagnosis to Classify Benign/Malignant Breast Mammogram Images.” 2014. Web. 21 Feb 2020.

Vancouver:

Aminikhanghahi S. FGMM-based Computer Aided Diagnosis to Classify Benign/Malignant Breast Mammogram Images. [Internet] [Masters thesis]. South Dakota State University; 2014. [cited 2020 Feb 21]. Available from: https://openprairie.sdstate.edu/etd/2074.

Council of Science Editors:

Aminikhanghahi S. FGMM-based Computer Aided Diagnosis to Classify Benign/Malignant Breast Mammogram Images. [Masters Thesis]. South Dakota State University; 2014. Available from: https://openprairie.sdstate.edu/etd/2074


Univerzitet u Beogradu

18. Jeftić, Branislava D., 1981-. Algoritam za određivanje biofizičkog stanja epitelnog tkiva na bazi spektroskopije.

Degree: Mašinski fakultet, 2018, Univerzitet u Beogradu

Oblast tehničkih nauka, Mašinstvo - Biomedicinsko inženjerstvo / Mechanical Engineering - Biomedical Engineering

Savremeni dijagnostički testovi koji se koriste u kliničkoj praksi imaju neosporan uticaj… (more)

Subjects/Keywords: Optomagnetic Spectroscopy; algorithm; cervical cancer; classification; screening; automated detection

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APA (6th Edition):

Jeftić, Branislava D., 1. (2018). Algoritam za određivanje biofizičkog stanja epitelnog tkiva na bazi spektroskopije. (Thesis). Univerzitet u Beogradu. Retrieved from https://fedorabg.bg.ac.rs/fedora/get/o:17656/bdef:Content/get

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Jeftić, Branislava D., 1981-. “Algoritam za određivanje biofizičkog stanja epitelnog tkiva na bazi spektroskopije.” 2018. Thesis, Univerzitet u Beogradu. Accessed February 21, 2020. https://fedorabg.bg.ac.rs/fedora/get/o:17656/bdef:Content/get.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Jeftić, Branislava D., 1981-. “Algoritam za određivanje biofizičkog stanja epitelnog tkiva na bazi spektroskopije.” 2018. Web. 21 Feb 2020.

Vancouver:

Jeftić, Branislava D. 1. Algoritam za određivanje biofizičkog stanja epitelnog tkiva na bazi spektroskopije. [Internet] [Thesis]. Univerzitet u Beogradu; 2018. [cited 2020 Feb 21]. Available from: https://fedorabg.bg.ac.rs/fedora/get/o:17656/bdef:Content/get.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Jeftić, Branislava D. 1. Algoritam za određivanje biofizičkog stanja epitelnog tkiva na bazi spektroskopije. [Thesis]. Univerzitet u Beogradu; 2018. Available from: https://fedorabg.bg.ac.rs/fedora/get/o:17656/bdef:Content/get

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Delft University of Technology

19. Dentro, S.C. Interpretable classification of tumours through multiple instance learning and somatic mutations :.

Degree: 2013, Delft University of Technology

 Next generation sequencing is brought into the clinic. Screening of disease associated genes will aid the diagnosis of disorders with a genetic component. The diagnosis… (more)

Subjects/Keywords: cancer; multiple instance learning; somatic mutations; classification; machine learning

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APA (6th Edition):

Dentro, S. C. (2013). Interpretable classification of tumours through multiple instance learning and somatic mutations :. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:e23175cb-d1a8-4cb6-af7b-9909f6412cf5

Chicago Manual of Style (16th Edition):

Dentro, S C. “Interpretable classification of tumours through multiple instance learning and somatic mutations :.” 2013. Masters Thesis, Delft University of Technology. Accessed February 21, 2020. http://resolver.tudelft.nl/uuid:e23175cb-d1a8-4cb6-af7b-9909f6412cf5.

MLA Handbook (7th Edition):

Dentro, S C. “Interpretable classification of tumours through multiple instance learning and somatic mutations :.” 2013. Web. 21 Feb 2020.

Vancouver:

Dentro SC. Interpretable classification of tumours through multiple instance learning and somatic mutations :. [Internet] [Masters thesis]. Delft University of Technology; 2013. [cited 2020 Feb 21]. Available from: http://resolver.tudelft.nl/uuid:e23175cb-d1a8-4cb6-af7b-9909f6412cf5.

Council of Science Editors:

Dentro SC. Interpretable classification of tumours through multiple instance learning and somatic mutations :. [Masters Thesis]. Delft University of Technology; 2013. Available from: http://resolver.tudelft.nl/uuid:e23175cb-d1a8-4cb6-af7b-9909f6412cf5


University of California – Irvine

20. Cao, Liyu. Support Vector Machine for Kidney Cancer Classification.

Degree: Biomedical Engineering, 2018, University of California – Irvine

 Renal cancer is the 12th leading cause of cancer death, accounting for 2.4 percent of all cancers in the United States. Two of most common… (more)

Subjects/Keywords: Biomedical engineering; Bioinformatics; Cancer; Classification; Kidney; Support vector machine

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APA (6th Edition):

Cao, L. (2018). Support Vector Machine for Kidney Cancer Classification. (Thesis). University of California – Irvine. Retrieved from http://www.escholarship.org/uc/item/2gg018np

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Cao, Liyu. “Support Vector Machine for Kidney Cancer Classification.” 2018. Thesis, University of California – Irvine. Accessed February 21, 2020. http://www.escholarship.org/uc/item/2gg018np.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Cao, Liyu. “Support Vector Machine for Kidney Cancer Classification.” 2018. Web. 21 Feb 2020.

Vancouver:

Cao L. Support Vector Machine for Kidney Cancer Classification. [Internet] [Thesis]. University of California – Irvine; 2018. [cited 2020 Feb 21]. Available from: http://www.escholarship.org/uc/item/2gg018np.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Cao L. Support Vector Machine for Kidney Cancer Classification. [Thesis]. University of California – Irvine; 2018. Available from: http://www.escholarship.org/uc/item/2gg018np

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Mississippi State University

21. Spencer, Vanda Victoria. A framework for improving breast cancer care decisions by using self-organizing maps to profile patients and quantify their attributes.

Degree: MS, Industrial and Systems Engineering, 2018, Mississippi State University

 Considering the commonality of breast cancer among women in the United States and the increasing popularity of precision medicine and data analytics in healthcare, the… (more)

Subjects/Keywords: self-organizing maps; breast cancer; classification; patient profile

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APA (6th Edition):

Spencer, V. V. (2018). A framework for improving breast cancer care decisions by using self-organizing maps to profile patients and quantify their attributes. (Masters Thesis). Mississippi State University. Retrieved from http://sun.library.msstate.edu/ETD-db/theses/available/etd-06122018-111848/ ;

Chicago Manual of Style (16th Edition):

Spencer, Vanda Victoria. “A framework for improving breast cancer care decisions by using self-organizing maps to profile patients and quantify their attributes.” 2018. Masters Thesis, Mississippi State University. Accessed February 21, 2020. http://sun.library.msstate.edu/ETD-db/theses/available/etd-06122018-111848/ ;.

MLA Handbook (7th Edition):

Spencer, Vanda Victoria. “A framework for improving breast cancer care decisions by using self-organizing maps to profile patients and quantify their attributes.” 2018. Web. 21 Feb 2020.

Vancouver:

Spencer VV. A framework for improving breast cancer care decisions by using self-organizing maps to profile patients and quantify their attributes. [Internet] [Masters thesis]. Mississippi State University; 2018. [cited 2020 Feb 21]. Available from: http://sun.library.msstate.edu/ETD-db/theses/available/etd-06122018-111848/ ;.

Council of Science Editors:

Spencer VV. A framework for improving breast cancer care decisions by using self-organizing maps to profile patients and quantify their attributes. [Masters Thesis]. Mississippi State University; 2018. Available from: http://sun.library.msstate.edu/ETD-db/theses/available/etd-06122018-111848/ ;


University of Waterloo

22. Pinto, Jeremy. Cancer Classification in Human Brain and Prostate Using Raman Spectroscopy and Machine Learning.

Degree: 2017, University of Waterloo

 Real-time assisted classification of cancerous and healthy human tissue is useful to surgeons since visual classification of cancer boundaries is almost impossible to the naked… (more)

Subjects/Keywords: Machine learning; Neural networks; Classification; Cancer; Raman Spectroscopy

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APA (6th Edition):

Pinto, J. (2017). Cancer Classification in Human Brain and Prostate Using Raman Spectroscopy and Machine Learning. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/12475

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Pinto, Jeremy. “Cancer Classification in Human Brain and Prostate Using Raman Spectroscopy and Machine Learning.” 2017. Thesis, University of Waterloo. Accessed February 21, 2020. http://hdl.handle.net/10012/12475.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Pinto, Jeremy. “Cancer Classification in Human Brain and Prostate Using Raman Spectroscopy and Machine Learning.” 2017. Web. 21 Feb 2020.

Vancouver:

Pinto J. Cancer Classification in Human Brain and Prostate Using Raman Spectroscopy and Machine Learning. [Internet] [Thesis]. University of Waterloo; 2017. [cited 2020 Feb 21]. Available from: http://hdl.handle.net/10012/12475.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Pinto J. Cancer Classification in Human Brain and Prostate Using Raman Spectroscopy and Machine Learning. [Thesis]. University of Waterloo; 2017. Available from: http://hdl.handle.net/10012/12475

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Tampere University

23. Bartaula, Jyoti Prasad. Classification Of Lymph Node Metastases In Breast Cancer With Features From Tissue Images Using Machine Learning Techniques .

Degree: 2017, Tampere University

 Determining the metastatic involvement of lymph node is very crucial in designing the treatment plans in breast cancer. Traditional way of detecting the lymph node… (more)

Subjects/Keywords: Lymph node metastasis; Breast cancer; Feature selection; Classification

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APA (6th Edition):

Bartaula, J. P. (2017). Classification Of Lymph Node Metastases In Breast Cancer With Features From Tissue Images Using Machine Learning Techniques . (Masters Thesis). Tampere University. Retrieved from https://trepo.tuni.fi/handle/10024/101726

Chicago Manual of Style (16th Edition):

Bartaula, Jyoti Prasad. “Classification Of Lymph Node Metastases In Breast Cancer With Features From Tissue Images Using Machine Learning Techniques .” 2017. Masters Thesis, Tampere University. Accessed February 21, 2020. https://trepo.tuni.fi/handle/10024/101726.

MLA Handbook (7th Edition):

Bartaula, Jyoti Prasad. “Classification Of Lymph Node Metastases In Breast Cancer With Features From Tissue Images Using Machine Learning Techniques .” 2017. Web. 21 Feb 2020.

Vancouver:

Bartaula JP. Classification Of Lymph Node Metastases In Breast Cancer With Features From Tissue Images Using Machine Learning Techniques . [Internet] [Masters thesis]. Tampere University; 2017. [cited 2020 Feb 21]. Available from: https://trepo.tuni.fi/handle/10024/101726.

Council of Science Editors:

Bartaula JP. Classification Of Lymph Node Metastases In Breast Cancer With Features From Tissue Images Using Machine Learning Techniques . [Masters Thesis]. Tampere University; 2017. Available from: https://trepo.tuni.fi/handle/10024/101726


Tampere University

24. Xu, Haifeng. An Evaluation of One Class Classifier on Gene Expression Data .

Degree: 2019, Tampere University

 It is not rare that medical data has imbalanced classes. This problem causes many difficulties when diagnosing rare diseases or cancer subtypes by machine learning… (more)

Subjects/Keywords: machine learning; bioinformatics; one-cass SVM; microarray; cancer classification

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APA (6th Edition):

Xu, H. (2019). An Evaluation of One Class Classifier on Gene Expression Data . (Masters Thesis). Tampere University. Retrieved from https://trepo.tuni.fi//handle/10024/116377

Chicago Manual of Style (16th Edition):

Xu, Haifeng. “An Evaluation of One Class Classifier on Gene Expression Data .” 2019. Masters Thesis, Tampere University. Accessed February 21, 2020. https://trepo.tuni.fi//handle/10024/116377.

MLA Handbook (7th Edition):

Xu, Haifeng. “An Evaluation of One Class Classifier on Gene Expression Data .” 2019. Web. 21 Feb 2020.

Vancouver:

Xu H. An Evaluation of One Class Classifier on Gene Expression Data . [Internet] [Masters thesis]. Tampere University; 2019. [cited 2020 Feb 21]. Available from: https://trepo.tuni.fi//handle/10024/116377.

Council of Science Editors:

Xu H. An Evaluation of One Class Classifier on Gene Expression Data . [Masters Thesis]. Tampere University; 2019. Available from: https://trepo.tuni.fi//handle/10024/116377


George Mason University

25. Dadkhah, Ezzat. Microbiome Analysis in Colorectal Cancer .

Degree: 2017, George Mason University

 Colorectal cancer (CRC) results from a complex interplay between genes and the environment. Recent studies have focused on the gut microbial population (the microbiota) and… (more)

Subjects/Keywords: Biology; Bioinformatics; Classification; Colorectal cancer; Machine learning; Microbiome; OTU; Statistical tests

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Dadkhah, E. (2017). Microbiome Analysis in Colorectal Cancer . (Thesis). George Mason University. Retrieved from http://hdl.handle.net/1920/11285

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Dadkhah, Ezzat. “Microbiome Analysis in Colorectal Cancer .” 2017. Thesis, George Mason University. Accessed February 21, 2020. http://hdl.handle.net/1920/11285.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Dadkhah, Ezzat. “Microbiome Analysis in Colorectal Cancer .” 2017. Web. 21 Feb 2020.

Vancouver:

Dadkhah E. Microbiome Analysis in Colorectal Cancer . [Internet] [Thesis]. George Mason University; 2017. [cited 2020 Feb 21]. Available from: http://hdl.handle.net/1920/11285.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Dadkhah E. Microbiome Analysis in Colorectal Cancer . [Thesis]. George Mason University; 2017. Available from: http://hdl.handle.net/1920/11285

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Hong Kong

26. 梁熊顯.; Lang, Brian. Cancer staging for differentiated thyroid carcinoma.

Degree: Master of Surgery, 2006, University of Hong Kong

published_or_final_version

abstract

Surgery

Master

Master of Surgery

Subjects/Keywords: Thyroid gland - Cancer - Classification.; Thyroid gland - Cancer - Prognosis.

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APA (6th Edition):

梁熊顯.; Lang, B. (2006). Cancer staging for differentiated thyroid carcinoma. (Masters Thesis). University of Hong Kong. Retrieved from Lang, B. [梁熊顯]. (2006). Cancer staging for differentiated thyroid carcinoma. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. Retrieved from http://dx.doi.org/10.5353/th_b3691613 ; http://dx.doi.org/10.5353/th_b3691613 ; http://hdl.handle.net/10722/52799

Chicago Manual of Style (16th Edition):

梁熊顯.; Lang, Brian. “Cancer staging for differentiated thyroid carcinoma.” 2006. Masters Thesis, University of Hong Kong. Accessed February 21, 2020. Lang, B. [梁熊顯]. (2006). Cancer staging for differentiated thyroid carcinoma. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. Retrieved from http://dx.doi.org/10.5353/th_b3691613 ; http://dx.doi.org/10.5353/th_b3691613 ; http://hdl.handle.net/10722/52799.

MLA Handbook (7th Edition):

梁熊顯.; Lang, Brian. “Cancer staging for differentiated thyroid carcinoma.” 2006. Web. 21 Feb 2020.

Vancouver:

梁熊顯.; Lang B. Cancer staging for differentiated thyroid carcinoma. [Internet] [Masters thesis]. University of Hong Kong; 2006. [cited 2020 Feb 21]. Available from: Lang, B. [梁熊顯]. (2006). Cancer staging for differentiated thyroid carcinoma. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. Retrieved from http://dx.doi.org/10.5353/th_b3691613 ; http://dx.doi.org/10.5353/th_b3691613 ; http://hdl.handle.net/10722/52799.

Council of Science Editors:

梁熊顯.; Lang B. Cancer staging for differentiated thyroid carcinoma. [Masters Thesis]. University of Hong Kong; 2006. Available from: Lang, B. [梁熊顯]. (2006). Cancer staging for differentiated thyroid carcinoma. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. Retrieved from http://dx.doi.org/10.5353/th_b3691613 ; http://dx.doi.org/10.5353/th_b3691613 ; http://hdl.handle.net/10722/52799


Freie Universität Berlin

27. Amin Kotb, Waleed Farouk Mohamed. Core Klassifikation, DNA ploidie und HPV beim Lungen- und Kopf-Hals-Karzinom.

Degree: 2012, Freie Universität Berlin

 Lungen und Kopf-Hals-Karzinome haben ähnliche genotoxische Riskofaktoren. Während die Mehrzahl der Lungenkarzinome allein durch das Zigarettenrauchen verursacht wird, ist das Rauchen zusammen mit einem Alkoholabusus… (more)

Subjects/Keywords: Lung cancer; classification; Grading; DNA ploidy; HPV; Head and Neck cancer; 600 Technik, Medizin, angewandte Wissenschaften::610 Medizin und Gesundheit

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APA (6th Edition):

Amin Kotb, W. F. M. (2012). Core Klassifikation, DNA ploidie und HPV beim Lungen- und Kopf-Hals-Karzinom. (Thesis). Freie Universität Berlin. Retrieved from http://dx.doi.org/10.17169/refubium-7135

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Amin Kotb, Waleed Farouk Mohamed. “Core Klassifikation, DNA ploidie und HPV beim Lungen- und Kopf-Hals-Karzinom.” 2012. Thesis, Freie Universität Berlin. Accessed February 21, 2020. http://dx.doi.org/10.17169/refubium-7135.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Amin Kotb, Waleed Farouk Mohamed. “Core Klassifikation, DNA ploidie und HPV beim Lungen- und Kopf-Hals-Karzinom.” 2012. Web. 21 Feb 2020.

Vancouver:

Amin Kotb WFM. Core Klassifikation, DNA ploidie und HPV beim Lungen- und Kopf-Hals-Karzinom. [Internet] [Thesis]. Freie Universität Berlin; 2012. [cited 2020 Feb 21]. Available from: http://dx.doi.org/10.17169/refubium-7135.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Amin Kotb WFM. Core Klassifikation, DNA ploidie und HPV beim Lungen- und Kopf-Hals-Karzinom. [Thesis]. Freie Universität Berlin; 2012. Available from: http://dx.doi.org/10.17169/refubium-7135

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Cambridge

28. Baker, Simon. Semantic text classification for cancer text mining.

Degree: PhD, 2018, University of Cambridge

Cancer researchers and oncologists benefit greatly from text mining major knowledge sources in biomedicine such as PubMed. Fundamentally, text mining depends on accurate text classification.… (more)

Subjects/Keywords: Cancer; Text Mining; Machine Learning; Classification; Literature-based Discovery; Hallmarks of Cancer; Deep Learning; Artificial Intelligence

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APA (6th Edition):

Baker, S. (2018). Semantic text classification for cancer text mining. (Doctoral Dissertation). University of Cambridge. Retrieved from https://www.repository.cam.ac.uk/handle/1810/275838 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.744844

Chicago Manual of Style (16th Edition):

Baker, Simon. “Semantic text classification for cancer text mining.” 2018. Doctoral Dissertation, University of Cambridge. Accessed February 21, 2020. https://www.repository.cam.ac.uk/handle/1810/275838 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.744844.

MLA Handbook (7th Edition):

Baker, Simon. “Semantic text classification for cancer text mining.” 2018. Web. 21 Feb 2020.

Vancouver:

Baker S. Semantic text classification for cancer text mining. [Internet] [Doctoral dissertation]. University of Cambridge; 2018. [cited 2020 Feb 21]. Available from: https://www.repository.cam.ac.uk/handle/1810/275838 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.744844.

Council of Science Editors:

Baker S. Semantic text classification for cancer text mining. [Doctoral Dissertation]. University of Cambridge; 2018. Available from: https://www.repository.cam.ac.uk/handle/1810/275838 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.744844

29. Tartare, Guillaume. Contribution à l'analyse de l'IRM dynamique pour l'aide au diagnostic du cancer de la prostate : Contribution to dynamic MRI analyze for diagnosis support for the prostate cancer.

Degree: Docteur es, Automatique, Génie informatique, Traitement du signal et des Images, 2014, Littoral

Le cancer de la prostate est le cancer le plus fréquent chez les hommes. Son développement entraine une néo-angiogénèse qui modifie le réseau capillaire. Il… (more)

Subjects/Keywords: Cancer de la prostate; IRM dynamique; Modélisation pharmacocinétique; Classification spectrale; Prostate cancer; Dynamic contrast enhanced MR imaging; Pharmacokinetics modeling; Spectral culstering

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APA (6th Edition):

Tartare, G. (2014). Contribution à l'analyse de l'IRM dynamique pour l'aide au diagnostic du cancer de la prostate : Contribution to dynamic MRI analyze for diagnosis support for the prostate cancer. (Doctoral Dissertation). Littoral. Retrieved from http://www.theses.fr/2014DUNK0427

Chicago Manual of Style (16th Edition):

Tartare, Guillaume. “Contribution à l'analyse de l'IRM dynamique pour l'aide au diagnostic du cancer de la prostate : Contribution to dynamic MRI analyze for diagnosis support for the prostate cancer.” 2014. Doctoral Dissertation, Littoral. Accessed February 21, 2020. http://www.theses.fr/2014DUNK0427.

MLA Handbook (7th Edition):

Tartare, Guillaume. “Contribution à l'analyse de l'IRM dynamique pour l'aide au diagnostic du cancer de la prostate : Contribution to dynamic MRI analyze for diagnosis support for the prostate cancer.” 2014. Web. 21 Feb 2020.

Vancouver:

Tartare G. Contribution à l'analyse de l'IRM dynamique pour l'aide au diagnostic du cancer de la prostate : Contribution to dynamic MRI analyze for diagnosis support for the prostate cancer. [Internet] [Doctoral dissertation]. Littoral; 2014. [cited 2020 Feb 21]. Available from: http://www.theses.fr/2014DUNK0427.

Council of Science Editors:

Tartare G. Contribution à l'analyse de l'IRM dynamique pour l'aide au diagnostic du cancer de la prostate : Contribution to dynamic MRI analyze for diagnosis support for the prostate cancer. [Doctoral Dissertation]. Littoral; 2014. Available from: http://www.theses.fr/2014DUNK0427

30. Bendifallah, Sofiane. Prédiction et modélisation du risque dans le cancer de l'endomètre de stade précoce : Risk prediction and modeling in early stage endometrial cancer.

Degree: Docteur es, Santé publique-épidémiologie-science de l'information biomédicale, 2016, Université Pierre et Marie Curie – Paris VI

Le développement de nouvelles options thérapeutiques est à l’origine d’un changement de paradigme dans le processus de décision médicale. L'émergence de la médecine individualisée et… (more)

Subjects/Keywords: Cancer de l'endomètre; Médecine individualisée; Statut des ganglions; Récidive; Classification; Nomogramme; Endometrial cancer; Individual analysis; Population analysis; 616.994

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Bendifallah, S. (2016). Prédiction et modélisation du risque dans le cancer de l'endomètre de stade précoce : Risk prediction and modeling in early stage endometrial cancer. (Doctoral Dissertation). Université Pierre et Marie Curie – Paris VI. Retrieved from http://www.theses.fr/2016PA066319

Chicago Manual of Style (16th Edition):

Bendifallah, Sofiane. “Prédiction et modélisation du risque dans le cancer de l'endomètre de stade précoce : Risk prediction and modeling in early stage endometrial cancer.” 2016. Doctoral Dissertation, Université Pierre et Marie Curie – Paris VI. Accessed February 21, 2020. http://www.theses.fr/2016PA066319.

MLA Handbook (7th Edition):

Bendifallah, Sofiane. “Prédiction et modélisation du risque dans le cancer de l'endomètre de stade précoce : Risk prediction and modeling in early stage endometrial cancer.” 2016. Web. 21 Feb 2020.

Vancouver:

Bendifallah S. Prédiction et modélisation du risque dans le cancer de l'endomètre de stade précoce : Risk prediction and modeling in early stage endometrial cancer. [Internet] [Doctoral dissertation]. Université Pierre et Marie Curie – Paris VI; 2016. [cited 2020 Feb 21]. Available from: http://www.theses.fr/2016PA066319.

Council of Science Editors:

Bendifallah S. Prédiction et modélisation du risque dans le cancer de l'endomètre de stade précoce : Risk prediction and modeling in early stage endometrial cancer. [Doctoral Dissertation]. Université Pierre et Marie Curie – Paris VI; 2016. Available from: http://www.theses.fr/2016PA066319

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