Dr Azad Dehghan
Deepcognito
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
- 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
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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Clinical Temporal Expression Mining
The aim of this project is to extract mentions of temporal expressions in clinical narratives (and patient-generated data) using a combination of rule-based and machine-learning methods. We also aim to normalise those mentions through mapping them to their value (using the ISO-8601 representation (e.g. “2012-10-31T09:00″) and type (e.g. Date, Duration,…
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Contrasts and contradictions in scientific texts
Detecting and analysing contrasts and contradictions in scientific texts is essential for suggesting further research potentials and discoveries. Finding contrasts and contradictions in text by means of automatic methods is a relatively new area in text mining. Specifically, most biological text mining research has so far focused on mining affirmative…
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Text Analytics and Sentiment Analysis in Healthcare Web 2.0
Sentiment analysis is a field in computational linguistics involving identification, extraction and classification of opinions and emotions expressed in natural language. 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,…