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You searched for +publisher:"University of Manchester" +contributor:("Nenadic, Goran"). Showing records 1 – 12 of 12 total matches.

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1. Milosevic, Nikola Ljubisa. A multi-layered approach to information extraction from tables in biomedical documents.

Degree: 2018, University of Manchester

The quantity of literature in the biomedical domain is growing exponentially. It is becoming impossible for researchers to cope with this ever-increasing amount of information.… (more)

Subjects/Keywords: table mining; information extraction; text mining; natural language processing; literature mining; health informatics; data curation; machine learning; data annotation

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

APA (6th Edition):

Milosevic, N. L. (2018). A multi-layered approach to information extraction from tables in biomedical documents. (Doctoral Dissertation). University of Manchester. Retrieved from http://www.manchester.ac.uk/escholar/uk-ac-man-scw:314635

Chicago Manual of Style (16th Edition):

Milosevic, Nikola Ljubisa. “A multi-layered approach to information extraction from tables in biomedical documents.” 2018. Doctoral Dissertation, University of Manchester. Accessed August 13, 2020. http://www.manchester.ac.uk/escholar/uk-ac-man-scw:314635.

MLA Handbook (7th Edition):

Milosevic, Nikola Ljubisa. “A multi-layered approach to information extraction from tables in biomedical documents.” 2018. Web. 13 Aug 2020.

Vancouver:

Milosevic NL. A multi-layered approach to information extraction from tables in biomedical documents. [Internet] [Doctoral dissertation]. University of Manchester; 2018. [cited 2020 Aug 13]. Available from: http://www.manchester.ac.uk/escholar/uk-ac-man-scw:314635.

Council of Science Editors:

Milosevic NL. A multi-layered approach to information extraction from tables in biomedical documents. [Doctoral Dissertation]. University of Manchester; 2018. Available from: http://www.manchester.ac.uk/escholar/uk-ac-man-scw:314635

2. Sarafraz, Farzaneh. Finding Conflicting Statements in the Biomedical Literature.

Degree: 2012, University of Manchester

 The main archive of life sciences literature currently contains more than 18,000,000 references, and it is virtually impossible for any human to stay up-to-date with… (more)

Subjects/Keywords: Text Mining; Natural Language Processing; Information Extraction; Biomedical Text Mining; Bioinformatics; Negation; Contradiction; Contrast; Literature-based discovery; Molecular Event Extraction

…joint project with Martin Gerner (Faculty of Life Sciences, University of Manchester… …copyright or related rights in it (the “Copyright”) and s/he has given The University of… …Manchester certain rights to use such Copyright, including for administrative purposes. ii… 

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APA (6th Edition):

Sarafraz, F. (2012). Finding Conflicting Statements in the Biomedical Literature. (Doctoral Dissertation). University of Manchester. Retrieved from http://www.manchester.ac.uk/escholar/uk-ac-man-scw:157382

Chicago Manual of Style (16th Edition):

Sarafraz, Farzaneh. “Finding Conflicting Statements in the Biomedical Literature.” 2012. Doctoral Dissertation, University of Manchester. Accessed August 13, 2020. http://www.manchester.ac.uk/escholar/uk-ac-man-scw:157382.

MLA Handbook (7th Edition):

Sarafraz, Farzaneh. “Finding Conflicting Statements in the Biomedical Literature.” 2012. Web. 13 Aug 2020.

Vancouver:

Sarafraz F. Finding Conflicting Statements in the Biomedical Literature. [Internet] [Doctoral dissertation]. University of Manchester; 2012. [cited 2020 Aug 13]. Available from: http://www.manchester.ac.uk/escholar/uk-ac-man-scw:157382.

Council of Science Editors:

Sarafraz F. Finding Conflicting Statements in the Biomedical Literature. [Doctoral Dissertation]. University of Manchester; 2012. Available from: http://www.manchester.ac.uk/escholar/uk-ac-man-scw:157382

3. Awg Hj md apong, Rosyzie Anna. Mining Negation and Uncertainty in Social Healthcare Networks.

Degree: 2018, University of Manchester

 More Internet users, particularly patients are seeking medical information from others through healthcare social networks (HSNs). Extensive amount of online comments by patients (or patient… (more)

Subjects/Keywords: Mining Negation Uncertainty Social Healthcare Networks

…x28;the “Copyright”) and s/he has given The University of Manchester certain rights to… …University of Manchester for offering me a place. The University has enabled me to develop skills… 

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APA (6th Edition):

Awg Hj md apong, R. A. (2018). Mining Negation and Uncertainty in Social Healthcare Networks. (Doctoral Dissertation). University of Manchester. Retrieved from http://www.manchester.ac.uk/escholar/uk-ac-man-scw:314094

Chicago Manual of Style (16th Edition):

Awg Hj md apong, Rosyzie Anna. “Mining Negation and Uncertainty in Social Healthcare Networks.” 2018. Doctoral Dissertation, University of Manchester. Accessed August 13, 2020. http://www.manchester.ac.uk/escholar/uk-ac-man-scw:314094.

MLA Handbook (7th Edition):

Awg Hj md apong, Rosyzie Anna. “Mining Negation and Uncertainty in Social Healthcare Networks.” 2018. Web. 13 Aug 2020.

Vancouver:

Awg Hj md apong RA. Mining Negation and Uncertainty in Social Healthcare Networks. [Internet] [Doctoral dissertation]. University of Manchester; 2018. [cited 2020 Aug 13]. Available from: http://www.manchester.ac.uk/escholar/uk-ac-man-scw:314094.

Council of Science Editors:

Awg Hj md apong RA. Mining Negation and Uncertainty in Social Healthcare Networks. [Doctoral Dissertation]. University of Manchester; 2018. Available from: http://www.manchester.ac.uk/escholar/uk-ac-man-scw:314094


University of Manchester

4. Jamieson, Daniel. Text mining molecular interactions and their context for studying disease.

Degree: 2014, University of Manchester

Molecular interactions enable us to understand the complexity of the human living system and how it can be exploited or malfunction to cause disease. The… (more)

Subjects/Keywords: molecular interactions; text-mining; pain; pathogens; curation; protein-protein interactions; hiv

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APA (6th Edition):

Jamieson, D. (2014). Text mining molecular interactions and their context for studying disease. (Doctoral Dissertation). University of Manchester. Retrieved from http://www.manchester.ac.uk/escholar/uk-ac-man-scw:242593

Chicago Manual of Style (16th Edition):

Jamieson, Daniel. “Text mining molecular interactions and their context for studying disease.” 2014. Doctoral Dissertation, University of Manchester. Accessed August 13, 2020. http://www.manchester.ac.uk/escholar/uk-ac-man-scw:242593.

MLA Handbook (7th Edition):

Jamieson, Daniel. “Text mining molecular interactions and their context for studying disease.” 2014. Web. 13 Aug 2020.

Vancouver:

Jamieson D. Text mining molecular interactions and their context for studying disease. [Internet] [Doctoral dissertation]. University of Manchester; 2014. [cited 2020 Aug 13]. Available from: http://www.manchester.ac.uk/escholar/uk-ac-man-scw:242593.

Council of Science Editors:

Jamieson D. Text mining molecular interactions and their context for studying disease. [Doctoral Dissertation]. University of Manchester; 2014. Available from: http://www.manchester.ac.uk/escholar/uk-ac-man-scw:242593

5. Gerner, Lars Martin Anders. Integrating text-mining approaches to identify entities and extract events from the biomedical literature.

Degree: 2012, University of Manchester

The amount of biomedical literature available is increasing at an exponential rate and is becoming increasingly difficult to navigate. Text-mining methods can po-tentially mitigate this… (more)

Subjects/Keywords: Biomedical text mining

…qualification of The University of Manchester or any other University or Institute of learning… …University of Manchester certain rights to use such Copyright, including for administrative… …x28;University of Manchester), with slightly over half of the work performed by me. 15… …been very much colder without them. Finally, this work was funded by The University of… …Manchester, BBSRC, and BioMed Central, without whose support this project would not have happened… 

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APA (6th Edition):

Gerner, L. M. A. (2012). Integrating text-mining approaches to identify entities and extract events from the biomedical literature. (Doctoral Dissertation). University of Manchester. Retrieved from http://www.manchester.ac.uk/escholar/uk-ac-man-scw:158970

Chicago Manual of Style (16th Edition):

Gerner, Lars Martin Anders. “Integrating text-mining approaches to identify entities and extract events from the biomedical literature.” 2012. Doctoral Dissertation, University of Manchester. Accessed August 13, 2020. http://www.manchester.ac.uk/escholar/uk-ac-man-scw:158970.

MLA Handbook (7th Edition):

Gerner, Lars Martin Anders. “Integrating text-mining approaches to identify entities and extract events from the biomedical literature.” 2012. Web. 13 Aug 2020.

Vancouver:

Gerner LMA. Integrating text-mining approaches to identify entities and extract events from the biomedical literature. [Internet] [Doctoral dissertation]. University of Manchester; 2012. [cited 2020 Aug 13]. Available from: http://www.manchester.ac.uk/escholar/uk-ac-man-scw:158970.

Council of Science Editors:

Gerner LMA. Integrating text-mining approaches to identify entities and extract events from the biomedical literature. [Doctoral Dissertation]. University of Manchester; 2012. Available from: http://www.manchester.ac.uk/escholar/uk-ac-man-scw:158970


University of Manchester

6. Karystianis, George. Extraction and representation of key characteristics from epidemiological literature.

Degree: 2014, University of Manchester

 Epidemiological studies are rich in information that could improve the understanding of concept complexity of a health problem, and are important sources for evidence based… (more)

Subjects/Keywords: text mining; epidemiology; concept map; key characteristics

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APA (6th Edition):

Karystianis, G. (2014). Extraction and representation of key characteristics from epidemiological literature. (Doctoral Dissertation). University of Manchester. Retrieved from http://www.manchester.ac.uk/escholar/uk-ac-man-scw:220558

Chicago Manual of Style (16th Edition):

Karystianis, George. “Extraction and representation of key characteristics from epidemiological literature.” 2014. Doctoral Dissertation, University of Manchester. Accessed August 13, 2020. http://www.manchester.ac.uk/escholar/uk-ac-man-scw:220558.

MLA Handbook (7th Edition):

Karystianis, George. “Extraction and representation of key characteristics from epidemiological literature.” 2014. Web. 13 Aug 2020.

Vancouver:

Karystianis G. Extraction and representation of key characteristics from epidemiological literature. [Internet] [Doctoral dissertation]. University of Manchester; 2014. [cited 2020 Aug 13]. Available from: http://www.manchester.ac.uk/escholar/uk-ac-man-scw:220558.

Council of Science Editors:

Karystianis G. Extraction and representation of key characteristics from epidemiological literature. [Doctoral Dissertation]. University of Manchester; 2014. Available from: http://www.manchester.ac.uk/escholar/uk-ac-man-scw:220558

7. Dehghan, Azad. Mining Patient Journeys From Healthcare Narratives.

Degree: 2015, University of Manchester

 The aim of the thesis is to investigate the feasibility of using text mining methods to reconstruct patient journeys from unstructured clinical narratives.A novel method… (more)

Subjects/Keywords: Clinical Text Mining; Temporal Text Mining; Natural Language Processing; Patient Journey; Patient Pathway; Clinical Pathway

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APA (6th Edition):

Dehghan, A. (2015). Mining Patient Journeys From Healthcare Narratives. (Doctoral Dissertation). University of Manchester. Retrieved from http://www.manchester.ac.uk/escholar/uk-ac-man-scw:266501

Chicago Manual of Style (16th Edition):

Dehghan, Azad. “Mining Patient Journeys From Healthcare Narratives.” 2015. Doctoral Dissertation, University of Manchester. Accessed August 13, 2020. http://www.manchester.ac.uk/escholar/uk-ac-man-scw:266501.

MLA Handbook (7th Edition):

Dehghan, Azad. “Mining Patient Journeys From Healthcare Narratives.” 2015. Web. 13 Aug 2020.

Vancouver:

Dehghan A. Mining Patient Journeys From Healthcare Narratives. [Internet] [Doctoral dissertation]. University of Manchester; 2015. [cited 2020 Aug 13]. Available from: http://www.manchester.ac.uk/escholar/uk-ac-man-scw:266501.

Council of Science Editors:

Dehghan A. Mining Patient Journeys From Healthcare Narratives. [Doctoral Dissertation]. University of Manchester; 2015. Available from: http://www.manchester.ac.uk/escholar/uk-ac-man-scw:266501


University of Manchester

8. Filannino, Michele. Data-driven Temporal Information Extraction with Applications in General and Clinical Domains.

Degree: 2016, University of Manchester

The automatic extraction of temporal information from written texts is pivotal for many Natural Language Processing applications such as question answering, text summarisation and information… (more)

Subjects/Keywords: text mining; machine learning; temporal information extraction

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APA (6th Edition):

Filannino, M. (2016). Data-driven Temporal Information Extraction with Applications in General and Clinical Domains. (Doctoral Dissertation). University of Manchester. Retrieved from http://www.manchester.ac.uk/escholar/uk-ac-man-scw:296972

Chicago Manual of Style (16th Edition):

Filannino, Michele. “Data-driven Temporal Information Extraction with Applications in General and Clinical Domains.” 2016. Doctoral Dissertation, University of Manchester. Accessed August 13, 2020. http://www.manchester.ac.uk/escholar/uk-ac-man-scw:296972.

MLA Handbook (7th Edition):

Filannino, Michele. “Data-driven Temporal Information Extraction with Applications in General and Clinical Domains.” 2016. Web. 13 Aug 2020.

Vancouver:

Filannino M. Data-driven Temporal Information Extraction with Applications in General and Clinical Domains. [Internet] [Doctoral dissertation]. University of Manchester; 2016. [cited 2020 Aug 13]. Available from: http://www.manchester.ac.uk/escholar/uk-ac-man-scw:296972.

Council of Science Editors:

Filannino M. Data-driven Temporal Information Extraction with Applications in General and Clinical Domains. [Doctoral Dissertation]. University of Manchester; 2016. Available from: http://www.manchester.ac.uk/escholar/uk-ac-man-scw:296972


University of Manchester

9. Mohamed Zaki ali, Mona Hussein. Investigating Data Quality in Question and Answer Reports.

Degree: 2016, University of Manchester

 Data Quality (DQ) has been a long-standing concern for a number of stakeholders in a variety of domains. It has become a critically important factor… (more)

Subjects/Keywords: data quality, data analysis, natural language processing, data mining, text mining; data quality methodology, question and answer reports, question and answer questionnaires

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APA (6th Edition):

Mohamed Zaki ali, M. H. (2016). Investigating Data Quality in Question and Answer Reports. (Doctoral Dissertation). University of Manchester. Retrieved from http://www.manchester.ac.uk/escholar/uk-ac-man-scw:302156

Chicago Manual of Style (16th Edition):

Mohamed Zaki ali, Mona Hussein. “Investigating Data Quality in Question and Answer Reports.” 2016. Doctoral Dissertation, University of Manchester. Accessed August 13, 2020. http://www.manchester.ac.uk/escholar/uk-ac-man-scw:302156.

MLA Handbook (7th Edition):

Mohamed Zaki ali, Mona Hussein. “Investigating Data Quality in Question and Answer Reports.” 2016. Web. 13 Aug 2020.

Vancouver:

Mohamed Zaki ali MH. Investigating Data Quality in Question and Answer Reports. [Internet] [Doctoral dissertation]. University of Manchester; 2016. [cited 2020 Aug 13]. Available from: http://www.manchester.ac.uk/escholar/uk-ac-man-scw:302156.

Council of Science Editors:

Mohamed Zaki ali MH. Investigating Data Quality in Question and Answer Reports. [Doctoral Dissertation]. University of Manchester; 2016. Available from: http://www.manchester.ac.uk/escholar/uk-ac-man-scw:302156

10. Wu, Chengkun. Using large-scale text mining for a systematic reconstruction of molecular mechanisms of diseases: a case study in thyroid cancer.

Degree: 2014, University of Manchester

Information about genes and pathways involved in a disease is usually 'buried' in scientific literature, making it difficult to perform systematic studies for a comprehensive… (more)

…thesis submitted to the University of Manchester for the degree of Doctor of Philosophy, 2014… …of The University of Manchester or any other University or Institute of learning… …University of Manchester certain rights to use such Copyright, including for administrative… …me to do my PhD in The University of Manchester under the Systems Biology DTC programme and… …gave me a lot of suggestions and help over the years. Finally, The University of Manchester… 

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APA (6th Edition):

Wu, C. (2014). Using large-scale text mining for a systematic reconstruction of molecular mechanisms of diseases: a case study in thyroid cancer. (Doctoral Dissertation). University of Manchester. Retrieved from http://www.manchester.ac.uk/escholar/uk-ac-man-scw:241289

Chicago Manual of Style (16th Edition):

Wu, Chengkun. “Using large-scale text mining for a systematic reconstruction of molecular mechanisms of diseases: a case study in thyroid cancer.” 2014. Doctoral Dissertation, University of Manchester. Accessed August 13, 2020. http://www.manchester.ac.uk/escholar/uk-ac-man-scw:241289.

MLA Handbook (7th Edition):

Wu, Chengkun. “Using large-scale text mining for a systematic reconstruction of molecular mechanisms of diseases: a case study in thyroid cancer.” 2014. Web. 13 Aug 2020.

Vancouver:

Wu C. Using large-scale text mining for a systematic reconstruction of molecular mechanisms of diseases: a case study in thyroid cancer. [Internet] [Doctoral dissertation]. University of Manchester; 2014. [cited 2020 Aug 13]. Available from: http://www.manchester.ac.uk/escholar/uk-ac-man-scw:241289.

Council of Science Editors:

Wu C. Using large-scale text mining for a systematic reconstruction of molecular mechanisms of diseases: a case study in thyroid cancer. [Doctoral Dissertation]. University of Manchester; 2014. Available from: http://www.manchester.ac.uk/escholar/uk-ac-man-scw:241289


University of Manchester

11. Stoney, Ruth. Using pathway networks to model context dependent cellular function.

Degree: 2018, University of Manchester

 Molecular networks are commonly used to explore cellular organisation and disease mechanisms. Function is studied using molecular interaction networks, such as protein-protein networks. Although much… (more)

Subjects/Keywords: bioinformatics; network; pathway; function

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APA (6th Edition):

Stoney, R. (2018). Using pathway networks to model context dependent cellular function. (Doctoral Dissertation). University of Manchester. Retrieved from http://www.manchester.ac.uk/escholar/uk-ac-man-scw:313097

Chicago Manual of Style (16th Edition):

Stoney, Ruth. “Using pathway networks to model context dependent cellular function.” 2018. Doctoral Dissertation, University of Manchester. Accessed August 13, 2020. http://www.manchester.ac.uk/escholar/uk-ac-man-scw:313097.

MLA Handbook (7th Edition):

Stoney, Ruth. “Using pathway networks to model context dependent cellular function.” 2018. Web. 13 Aug 2020.

Vancouver:

Stoney R. Using pathway networks to model context dependent cellular function. [Internet] [Doctoral dissertation]. University of Manchester; 2018. [cited 2020 Aug 13]. Available from: http://www.manchester.ac.uk/escholar/uk-ac-man-scw:313097.

Council of Science Editors:

Stoney R. Using pathway networks to model context dependent cellular function. [Doctoral Dissertation]. University of Manchester; 2018. Available from: http://www.manchester.ac.uk/escholar/uk-ac-man-scw:313097

12. Duck, Geraint. Extraction of database and software usage patterns from the bioinformatics literature.

Degree: 2015, University of Manchester

 Method forms the basis of scientific research, enabling criticism, selection and extension of current knowledge. However, methods are usually confined to the literature, where they… (more)

Subjects/Keywords: bioinformatics; resources; databases; software; methods; usage patterns; text-mining; usage networks; computational biology; resource names

…IOINFORMATICS L ITERATURE Geraint James Duck A thesis submitted to the University of Manchester for… …x29; and s/he has given The University of Manchester certain rights to use such Copyright… …last four years at the University of Manchester working on his PhD, the outcome of which is… …Bioinformatics at the University of Manchester. For his MSc dissertation, he investigated a statistical… …the literature. Poster, November 2011. Presented at The University of Manchester Symposium… 

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

APA (6th Edition):

Duck, G. (2015). Extraction of database and software usage patterns from the bioinformatics literature. (Doctoral Dissertation). University of Manchester. Retrieved from http://www.manchester.ac.uk/escholar/uk-ac-man-scw:259870

Chicago Manual of Style (16th Edition):

Duck, Geraint. “Extraction of database and software usage patterns from the bioinformatics literature.” 2015. Doctoral Dissertation, University of Manchester. Accessed August 13, 2020. http://www.manchester.ac.uk/escholar/uk-ac-man-scw:259870.

MLA Handbook (7th Edition):

Duck, Geraint. “Extraction of database and software usage patterns from the bioinformatics literature.” 2015. Web. 13 Aug 2020.

Vancouver:

Duck G. Extraction of database and software usage patterns from the bioinformatics literature. [Internet] [Doctoral dissertation]. University of Manchester; 2015. [cited 2020 Aug 13]. Available from: http://www.manchester.ac.uk/escholar/uk-ac-man-scw:259870.

Council of Science Editors:

Duck G. Extraction of database and software usage patterns from the bioinformatics literature. [Doctoral Dissertation]. University of Manchester; 2015. Available from: http://www.manchester.ac.uk/escholar/uk-ac-man-scw:259870

.