CRIS Projects Details -
Accept Cookies

Cookies: How we use information on our website:

We use cookies on our website to make it clear, useful and reliable. In order to achieve this and to provide certain personalised features we store a small amount
of data about you. Click Here to learn more. By navigating from the front page to other sections of our website, you are consenting to information being stored.


CRIS Projects Details

Project Details

 

Determining temporal information in clinical text

Lead Applicant Name :
Sumithra Velupillai
Project Type :
Research
Approval Date :
10-Jul-2018
References :
Viani N, Botelle R, Kerwin J, Lin L, Patel R, Stewart R, Velupillai S. (2020) A Natural Language Processing Approach for Identifying Temporal Disease Onset Information from Mental Healthcare Text. Scientific Reports.<br/><br/>Viani N, Kam J, Yin L, Bittar A, Dutta R, Patel R, Stewart R, Velupillai S. (2020) Temporal Information Extraction from Mental Health Records to Identify Duration of Untreated Psychosis. Journal of biomedical semantics
Lay Summary :
Natural language processing techniques have been successfully developed to extract clinical concepts such as symptoms (hallucinations), treatments (clozapine) and diagnoses (schizophrenia) from health record text such as data from CRIS, but these methods don’t currently capture the timing of these events. We will seek to develop methods that can ascertain when a symptom or treatment happened, finding time information (dates, durations), relevant concepts (symptoms, treatments), and linking these together.<br/>

< Back to search