Automated Construction of Lexicons to Improve Depression Screening With Text Messages

Given that depression is one of the most prevalent mental illnesses, developing effective and unobtrusive diagnosis tools is of great importance. Recent work that screens for depression with text messages leverage models relying on lexical category features. Given the colloquial nature of text messa...

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Veröffentlicht in:	IEEE journal of biomedical and health informatics 2023-06, Vol.27 (6), p.2751-2759
Hauptverfasser:	Tlachac, ML, Shrestha, Avantika, Shah, Mahum, Litterer, Benjamin, Rundensteiner, Elke A.
Format:	Artikel
Sprache:	eng
Schlagworte:	Depression Depression - diagnosis digital phenotype Electronic mail Feature extraction Humans Language Learning algorithms Machine Learning Medical screening Mental depression Mental Disorders - diagnosis Messages Mobile health Natural language processing Performance enhancement Social networking (online) Software super- vised machine learning Text categorization text classification Text Messaging
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