Implementing machine learning algorithms for suicide risk prediction in clinical practice: A focus group study

Abstract excerpt

<p>Background: Interest in developing machine learning algorithms that use electronic health record data to predict patients’ risk of suicidal behavior has recently proliferated. Whether and how such models might be implemented and useful in clinical practice, however, remains unknown. In order to ultimately make automated suicide risk prediction algorithms useful in practice, and thus better prevent patient suici...

Topics

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• Algorithms
• Data Mining
• Electronic Health Records
• International Classification of Diseases
• Machine Learning
• Natural Language Processing
• ROC Curve
• Suicide, Attempted

Identifiers and source

Literature Corpus work

0629e93c-d8c1-5cd2-87a3-1a2f200c3595

DOI

10.31234/osf.io/6m5qd