Text Classification to Inform Suicide Risk Assessment in Electronic Health Records

Studies in health technology and informatics, pp. 40-44, 2019.

Cited by: 0|Bibtex|Views3|DOI:https://doi.org/10.3233/SHTI190179
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Other Links: pubmed.ncbi.nlm.nih.gov|dblp.uni-trier.de

Abstract:

Assessing a patient's risk of an impending suicide attempt has been hampered by limited information about dynamic factors that change rapidly in the days leading up to an attempt. The storage of patient data in electronic health records (EHRs) has facilitated population-level risk assessment studies using machine learning techniques. Unti...More

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