Identifying First Episodes of Psychosis in Psychiatric Patient Records using Machine Learning

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Gorrell, Genevive, Oduola, Sherifat ORCID: https://orcid.org/0000-0002-7227-9536, Roberts, Angus, Craig, Thomas, Morgan, Craig and Stewart, Rob (2016) Identifying First Episodes of Psychosis in Psychiatric Patient Records using Machine Learning. In: 15th Workshop on Biomedical Natural Language Processing, 2016-08-12.

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Abstract

Natural language processing is being pressed into use to facilitate the selection of cases for medical research in electronic health record databases, though study inclusion criteria may be complex, and the linguistic cues indicating eligibility may be subtle. Finding cases of first episode psychosis raised a number of problems for automated approaches, providing an opportunity to explore how machine learning technologies might be used to overcome them. A system was delivered that achieved an AUC of 0.85, enabling 95% of relevant cases to be identified whilst halving the work required in manually reviewing cases. The techniques that made this possible are presented.

Item Type:	Conference or Workshop Item (Paper)
Faculty \ School:	Faculty of Medicine and Health Sciences > School of Health Sciences
UEA Research Groups:	Faculty of Medicine and Health Sciences > Research Groups > Health Promotion Faculty of Science > Research Groups > Norwich Epidemiology Centre Faculty of Medicine and Health Sciences > Research Groups > Norwich Epidemiology Centre Faculty of Medicine and Health Sciences > Research Centres > Population Health
Related URLs:	http://www.aclweb.org/anthology/W16-2927
Depositing User:	Pure Connector
Date Deposited:	11 Jun 2018 14:34
Last Modified:	19 Oct 2023 04:01
URI:	https://ueaeprints.uea.ac.uk/id/eprint/67344
DOI:

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