2011 – This year we took again part in the annual i2b2 shared task, an international text mining challenge in the clinical/health-care domain. The team composed of members from University of Novi Sad (Kovacevic, A.) and University of Manchester (Dehghan, A., Nenadic G. and Keane, J.). The aim of the challenge…
Natural Language Processing for Clinical Data: Continuous Success at i2b2 Challenges
2011 – This year we took again part in the annual i2b2 shared task, an international text mining challenge in the clinical/health-care domain. The team composed of members from University of Novi Sad (Kovacevic, A.) and University of Manchester (Dehghan, A., Nenadic G. and Keane, J.). The aim of the challenge…
Temporal expression extraction with extensive feature type selection and a posteriori label adjustment
Modelling and Extraction of Variability in Free-text Medication Prescriptions from an Anonymised Primary Care Electronic Medical Record Research Database
i2b2/UTHealth 2014
These are the rules and the dictionaries used in the i2b2/UTHealth 2014 Challenge in Natural Language Processing for Clinical Data. The task involved the identification of heart disease risk factors from longitudianl clinical notes of diabetic records. The methodology is knowledge-driven and the system implements local lexicalised rules (based on…
Using local lexicalized rules to identify heart disease risk factors in clinical notes
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…
Document clustering and summarisation
Document clustering is a generic problem with wide spread applications within Natural Language engineering. Present research focuses on using text summarization techniques as a pre-processing step for document clustering in the context of automated assessment of student essays. One of the major problems in natural language processing is that a…
Prof Goran Nenadic
Prof Goran Nenadic is Professor in the School of Computer Science, University of Manchester, a group leader in the Manchester Institute of Biotechnology (MIB) and Health eResearch Centre (HeRC).