Advanced search options

Advanced Search Options 🞨

Browse by author name (“Author name starts with…”).

Find ETDs with:

in
/  
in
/  
in
/  
in

Written in Published in Earliest date Latest date

Sorted by

Results per page:

Sorted by: relevance · author · university · dateNew search

You searched for subject:(Biomedical Knowledge Discovery). Showing records 1 – 8 of 8 total matches.

Search Limiters

Last 2 Years | English Only

No search limiters apply to these results.

▼ Search Limiters


Stellenbosch University

1. Arndt, Heidi. Knowledge discovery and anomalies — towards a dynamic decision-making model for medical informatics.

Degree: PhD, Information Science, 2018, Stellenbosch University

 ENGLISH SUMMARY : Worldwide healthcare has become a major concern for modern society, which is challenged to make quality care accessible and affordable to all.… (more)

Subjects/Keywords: Algorithmic knowledge discovery; Biomedical informatics; Complex organisations; Bisociative knowledge discovery; UCTD

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Arndt, H. (2018). Knowledge discovery and anomalies — towards a dynamic decision-making model for medical informatics. (Doctoral Dissertation). Stellenbosch University. Retrieved from http://hdl.handle.net/10019.1/103311

Chicago Manual of Style (16th Edition):

Arndt, Heidi. “Knowledge discovery and anomalies — towards a dynamic decision-making model for medical informatics.” 2018. Doctoral Dissertation, Stellenbosch University. Accessed August 12, 2020. http://hdl.handle.net/10019.1/103311.

MLA Handbook (7th Edition):

Arndt, Heidi. “Knowledge discovery and anomalies — towards a dynamic decision-making model for medical informatics.” 2018. Web. 12 Aug 2020.

Vancouver:

Arndt H. Knowledge discovery and anomalies — towards a dynamic decision-making model for medical informatics. [Internet] [Doctoral dissertation]. Stellenbosch University; 2018. [cited 2020 Aug 12]. Available from: http://hdl.handle.net/10019.1/103311.

Council of Science Editors:

Arndt H. Knowledge discovery and anomalies — towards a dynamic decision-making model for medical informatics. [Doctoral Dissertation]. Stellenbosch University; 2018. Available from: http://hdl.handle.net/10019.1/103311

2. Lefebvre, A.E. Reproducible Research and Interactive Data Mining in Bioinformatics.

Degree: 2015, Universiteit Utrecht

 Data analysis of Next-Generation sequencing data is widely recognized as being a bottleneck on the way to understanding the human genome and personalize treatments. Studies… (more)

Subjects/Keywords: Reproducible Research; Knowledge discovery; bioinformatics; biomedical science

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Lefebvre, A. E. (2015). Reproducible Research and Interactive Data Mining in Bioinformatics. (Masters Thesis). Universiteit Utrecht. Retrieved from http://dspace.library.uu.nl:8080/handle/1874/319430

Chicago Manual of Style (16th Edition):

Lefebvre, A E. “Reproducible Research and Interactive Data Mining in Bioinformatics.” 2015. Masters Thesis, Universiteit Utrecht. Accessed August 12, 2020. http://dspace.library.uu.nl:8080/handle/1874/319430.

MLA Handbook (7th Edition):

Lefebvre, A E. “Reproducible Research and Interactive Data Mining in Bioinformatics.” 2015. Web. 12 Aug 2020.

Vancouver:

Lefebvre AE. Reproducible Research and Interactive Data Mining in Bioinformatics. [Internet] [Masters thesis]. Universiteit Utrecht; 2015. [cited 2020 Aug 12]. Available from: http://dspace.library.uu.nl:8080/handle/1874/319430.

Council of Science Editors:

Lefebvre AE. Reproducible Research and Interactive Data Mining in Bioinformatics. [Masters Thesis]. Universiteit Utrecht; 2015. Available from: http://dspace.library.uu.nl:8080/handle/1874/319430


RMIT University

3. Forkan, A. A cloud-based, predictive and context-aware system for ambient assisted living.

Degree: 2016, RMIT University

 Ambient assisted living (AAL) technology provides the opportunity for people with disabilities or chronic medical conditions to lead independent lives in their home, relying on… (more)

Subjects/Keywords: Fields of Research; Remote healthcare; Big biomedical data; Change detection; Knowledge discovery; Ambient assisted living

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Forkan, A. (2016). A cloud-based, predictive and context-aware system for ambient assisted living. (Thesis). RMIT University. Retrieved from http://researchbank.rmit.edu.au/view/rmit:161844

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):

Forkan, A. “A cloud-based, predictive and context-aware system for ambient assisted living.” 2016. Thesis, RMIT University. Accessed August 12, 2020. http://researchbank.rmit.edu.au/view/rmit:161844.

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

MLA Handbook (7th Edition):

Forkan, A. “A cloud-based, predictive and context-aware system for ambient assisted living.” 2016. Web. 12 Aug 2020.

Vancouver:

Forkan A. A cloud-based, predictive and context-aware system for ambient assisted living. [Internet] [Thesis]. RMIT University; 2016. [cited 2020 Aug 12]. Available from: http://researchbank.rmit.edu.au/view/rmit:161844.

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

Council of Science Editors:

Forkan A. A cloud-based, predictive and context-aware system for ambient assisted living. [Thesis]. RMIT University; 2016. Available from: http://researchbank.rmit.edu.au/view/rmit:161844

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


The Ohio State University

4. Marsolo, Keith Allen. A workflow for the modeling and analysis of biomedical data.

Degree: PhD, Computer and Information Science, 2007, The Ohio State University

 The use of data mining techniques for the classification of shape and structure can provide critical results when applied biomedical data. On a molecular level,… (more)

Subjects/Keywords: Computer Science; Biomedical Data Modeling; Spatial Modeling; Biomedical Knowledge Discovery; Classification of Structure-based Data.; Bioinformatics; Protein Modeling; Protein Classification

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Marsolo, K. A. (2007). A workflow for the modeling and analysis of biomedical data. (Doctoral Dissertation). The Ohio State University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=osu1180309265

Chicago Manual of Style (16th Edition):

Marsolo, Keith Allen. “A workflow for the modeling and analysis of biomedical data.” 2007. Doctoral Dissertation, The Ohio State University. Accessed August 12, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=osu1180309265.

MLA Handbook (7th Edition):

Marsolo, Keith Allen. “A workflow for the modeling and analysis of biomedical data.” 2007. Web. 12 Aug 2020.

Vancouver:

Marsolo KA. A workflow for the modeling and analysis of biomedical data. [Internet] [Doctoral dissertation]. The Ohio State University; 2007. [cited 2020 Aug 12]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1180309265.

Council of Science Editors:

Marsolo KA. A workflow for the modeling and analysis of biomedical data. [Doctoral Dissertation]. The Ohio State University; 2007. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1180309265

5. Crichton, Gamal Kashaka Omari. Improving Automated Literature-based Discovery with Neural Networks: Neural biomedical Named Entity Recognition, Link Prediction and Discovery.

Degree: PhD, 2019, University of Cambridge

 Literature-based Discovery (LBD) uses information from explicit statements in literature to generate new or unstated knowledge. Automated LBD can thus facilitate hypothesis testing and generation… (more)

Subjects/Keywords: Literature-based Discovery; LBD; Neural networks; Named Entity Recognition; NER; Multi-task Learning; LION LBD; knowledge discovery; Natural Language Processing; NLP; Machine Learning; Deep Learning; Biomedical NLP; Biomedical Knowledge Discovery; Link Predcition; Language Technology Laboratory

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Crichton, G. K. O. (2019). Improving Automated Literature-based Discovery with Neural Networks: Neural biomedical Named Entity Recognition, Link Prediction and Discovery. (Doctoral Dissertation). University of Cambridge. Retrieved from https://www.repository.cam.ac.uk/handle/1810/293886

Chicago Manual of Style (16th Edition):

Crichton, Gamal Kashaka Omari. “Improving Automated Literature-based Discovery with Neural Networks: Neural biomedical Named Entity Recognition, Link Prediction and Discovery.” 2019. Doctoral Dissertation, University of Cambridge. Accessed August 12, 2020. https://www.repository.cam.ac.uk/handle/1810/293886.

MLA Handbook (7th Edition):

Crichton, Gamal Kashaka Omari. “Improving Automated Literature-based Discovery with Neural Networks: Neural biomedical Named Entity Recognition, Link Prediction and Discovery.” 2019. Web. 12 Aug 2020.

Vancouver:

Crichton GKO. Improving Automated Literature-based Discovery with Neural Networks: Neural biomedical Named Entity Recognition, Link Prediction and Discovery. [Internet] [Doctoral dissertation]. University of Cambridge; 2019. [cited 2020 Aug 12]. Available from: https://www.repository.cam.ac.uk/handle/1810/293886.

Council of Science Editors:

Crichton GKO. Improving Automated Literature-based Discovery with Neural Networks: Neural biomedical Named Entity Recognition, Link Prediction and Discovery. [Doctoral Dissertation]. University of Cambridge; 2019. Available from: https://www.repository.cam.ac.uk/handle/1810/293886


University of Cambridge

6. Crichton, Gamal Kashaka Omari. Improving automated literature-based discovery with neural networks : neural biomedical named entity recognition, link prediction and discovery.

Degree: PhD, 2019, University of Cambridge

 Literature-based Discovery (LBD) uses information from explicit statements in literature to generate new or unstated knowledge. Automated LBD can thus facilitate hypothesis testing and generation… (more)

Subjects/Keywords: Literature-based Discovery; LBD; Neural networks; Named Entity Recognition; NER; Multi-task Learning; LION LBD; knowledge discovery; Natural Language Processing; NLP; Machine Learning; Deep Learning; Biomedical NLP; Biomedical Knowledge Discovery; Link Predcition; Language Technology Laboratory

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Crichton, G. K. O. (2019). Improving automated literature-based discovery with neural networks : neural biomedical named entity recognition, link prediction and discovery. (Doctoral Dissertation). University of Cambridge. Retrieved from https://www.repository.cam.ac.uk/handle/1810/293886 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.782841

Chicago Manual of Style (16th Edition):

Crichton, Gamal Kashaka Omari. “Improving automated literature-based discovery with neural networks : neural biomedical named entity recognition, link prediction and discovery.” 2019. Doctoral Dissertation, University of Cambridge. Accessed August 12, 2020. https://www.repository.cam.ac.uk/handle/1810/293886 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.782841.

MLA Handbook (7th Edition):

Crichton, Gamal Kashaka Omari. “Improving automated literature-based discovery with neural networks : neural biomedical named entity recognition, link prediction and discovery.” 2019. Web. 12 Aug 2020.

Vancouver:

Crichton GKO. Improving automated literature-based discovery with neural networks : neural biomedical named entity recognition, link prediction and discovery. [Internet] [Doctoral dissertation]. University of Cambridge; 2019. [cited 2020 Aug 12]. Available from: https://www.repository.cam.ac.uk/handle/1810/293886 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.782841.

Council of Science Editors:

Crichton GKO. Improving automated literature-based discovery with neural networks : neural biomedical named entity recognition, link prediction and discovery. [Doctoral Dissertation]. University of Cambridge; 2019. Available from: https://www.repository.cam.ac.uk/handle/1810/293886 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.782841


Georgia Tech

7. Liu, Ying. Text Mining Biomedical Literature for Genomic Knowledge Discovery.

Degree: PhD, Computing, 2005, Georgia Tech

 The last decade has been marked by unprecedented growth in both the production of biomedical data and the amount of published literature discussing it. Almost… (more)

Subjects/Keywords: Text mining; Biomedical literature; Gene function; Clustering; Genomic knowledge discovery; Microarray

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Liu, Y. (2005). Text Mining Biomedical Literature for Genomic Knowledge Discovery. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/7242

Chicago Manual of Style (16th Edition):

Liu, Ying. “Text Mining Biomedical Literature for Genomic Knowledge Discovery.” 2005. Doctoral Dissertation, Georgia Tech. Accessed August 12, 2020. http://hdl.handle.net/1853/7242.

MLA Handbook (7th Edition):

Liu, Ying. “Text Mining Biomedical Literature for Genomic Knowledge Discovery.” 2005. Web. 12 Aug 2020.

Vancouver:

Liu Y. Text Mining Biomedical Literature for Genomic Knowledge Discovery. [Internet] [Doctoral dissertation]. Georgia Tech; 2005. [cited 2020 Aug 12]. Available from: http://hdl.handle.net/1853/7242.

Council of Science Editors:

Liu Y. Text Mining Biomedical Literature for Genomic Knowledge Discovery. [Doctoral Dissertation]. Georgia Tech; 2005. Available from: http://hdl.handle.net/1853/7242

8. Vladutu, Liviu - Mihai. Computational intelligence methods on biomedical signal analysis and data mining in medical records.

Degree: 2004, University of Patras; Πανεπιστήμιο Πατρών

Subjects/Keywords: Υπολογιστική νοημοσύνη; Ανάλυση βιοϊατρικού σήματος; Εξαγωγή γνώσης από δεδομένα; Μέθοδοι ομαδοποίησης; Ανίχνευση ισχαιμίας; Κ - παράθυρο; Νευρωνικά δίκτυα; Γενικευμένες ακτινικές συναρτήσεις; Computational intelligence; Biomedical signal analysis; Knowledge discovery in databases; Clustering methods; Ischemia detection; K - windows; Neural networks; Generalized radial basis functions

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Vladutu, L. -. M. (2004). Computational intelligence methods on biomedical signal analysis and data mining in medical records. (Thesis). University of Patras; Πανεπιστήμιο Πατρών. Retrieved from http://hdl.handle.net/10442/hedi/26705

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):

Vladutu, Liviu - Mihai. “Computational intelligence methods on biomedical signal analysis and data mining in medical records.” 2004. Thesis, University of Patras; Πανεπιστήμιο Πατρών. Accessed August 12, 2020. http://hdl.handle.net/10442/hedi/26705.

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

MLA Handbook (7th Edition):

Vladutu, Liviu - Mihai. “Computational intelligence methods on biomedical signal analysis and data mining in medical records.” 2004. Web. 12 Aug 2020.

Vancouver:

Vladutu L-M. Computational intelligence methods on biomedical signal analysis and data mining in medical records. [Internet] [Thesis]. University of Patras; Πανεπιστήμιο Πατρών; 2004. [cited 2020 Aug 12]. Available from: http://hdl.handle.net/10442/hedi/26705.

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

Council of Science Editors:

Vladutu L-M. Computational intelligence methods on biomedical signal analysis and data mining in medical records. [Thesis]. University of Patras; Πανεπιστήμιο Πατρών; 2004. Available from: http://hdl.handle.net/10442/hedi/26705

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

.