Prof John Keane
Professor of Data Engineering (Computing Science)
Publications
- Combining knowledge- and data-driven methods for de-identification of clinical narratives
Journal of Biomedical Informatics. Academic Press; 2015
- Using local lexicalized rules to identify heart disease risk factors in clinical notes
Journal of Biomedical Informatics. Academic Press; 2015
- An ontological approach to knowledge management for sustainable nuclear decommissioning
International Journal of Nuclear Knowledge Management. Inderscience Publishers; 2014
- Text mining of cancer-related information: Review of current status and future directions
International Journal of Medical Informatics. Elsevier Ireland Ltd; 2014
- Combining rules and machine learning for extraction of temporal expressions and events from clinical narratives
Journal of the American Medical Informatics Association; 2013
- Topic Categorisation of Statements in Suicide Notes with Integrated Rules and Machine Learning
Biomedical Informatics Insight. Libertas Academica Ltd.; 2012
- Development of a Computerized Decision Support System for Treatment Planning and Outcome Prediction in Aneurysmal Subarachnoid Haemorrhage
Proceedings of American Society of NeuroRadiologists 48th Annual Meeting: American Society of NeuroRadiologists 48th Annual Meeting (ASNR 2010). Boston, UK; 2010
- Early Phase Validation of a Decision Support System within the Exemplar of Aneurysmal Subarachnoid Haemorrhage
Proceedings of British Society of NeuroRadiologists Annual Conference (BSNR 2010) : British Society of NeuroRadiologists Annual Conference (BSNR 2010) . Glasgow, UK; 2010
- Decision Support Systems for Clinical Radiological Practice
British Journal of Radiology; 2010
- Medication Information Extraction with Linguistic Pattern Matching and Semantic Rules
J Am Med Inform Assoc. ; 2010
- Combining Lexical Profiling, Rules and Machine Learning for Disease Prediction from Hospital Discharge Summaries
Proc. of i2b2 Obesity Challenge 2008: i2b2 Obesity Challenge 2008; 2008
- Computational Treatment Prediction of Subarachnoid Haemorrhage
British Society of Neuroradiologists (BSNR) 2008. Manchester; 2008
- Assigning Roles to Protein Mentions: the Case of Transcription Factors
Journal of Biomedical Informatics; 2009
- A cascaded approach to normalizing gene mentions in biomedical literature
Bioinformation; 2007
- Development of a Language-based Bayesian Decision Support System for Treatment Planning and Outcome Prediction in Aneurysmal Subarachnoid Haemorrhage
BSNR 2008. London, UK; 2008
- Decision support system for treatment planning and outcome prediction in aneurysmal subarachnoid haemorrhage
Computer Assisted Radiology and Surgery 2008. Barcelona; 2008
- A Text Mining Approach to the Prediction of Disease Status from Clinical Discharge Summaries
Journal of the American Medical Informatics Association. BMJ Publishing Group; 2009
- Identification of transcription factor contexts in literature using machine learning approaches
BMC Bioinformatics; 2008
- Identification of transcription factor contexts in literature using machine learning approaches
2nd International Symposium on Languages in Biology and Medicine: 2nd International Symposium on Languages in Biology and Medicine. Singapore, SINGAPORE. Biomed Central Ltd; 2007
Projects
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Healthcare text mining projects: mining clinical narratives and patient-generated data
We currently run a number of projects to extract various structured data from unstructured clinical narratives and electronic healthcare records (EHRs). In previous projects we have developed a combination of rule-based and machine-learning methods to identify diseses that a patient has or does not have (“disease status”), including identification of…
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Blog sentiment analysis
Sentiment analysis is the extraction of attitudes and opinions from human-authored documents. The capture and analysis of such attitudes and opinions in an automated and structured fashion might offer a powerful technology to a number of problem domains, including business intelligence, marketing, national security, and crime prevention. This project aims…