Prediction of psychosis across protocols and risk cohorts using automated language analysis

By Cheryl Corcoran, Facundo Carrillo, Diego Fernández-Slezak, Gillinder Bedi, C. Klim, Daniel C. Javitt, C. Bearden, G. Cecchi. World Psychiatry, 2018

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Precision Medicine, AI, and the Future of Personalized Health Care (2020, background): “80–83 Efforts also are underway to detect changes in mental health using smartphone sensors.”
Artificial Intelligence for Mental Healthcare: Clinical Applications, Barriers, Facilitators, and Artificial Wisdom (2021, background): “Illustrations include Instagram photographs to predict risk of developing depression (51), speech data to predict psychosis onset in high-risk youth (52), and identifying individuals with PTSD (53).”
Using clinical Natural Language Processing for health outcomes research: Overview and actionable suggestions for future advances (2018, neutral): “NLP methods are usually developed to identify and classify instances of some clinically relevant phenomenon at a sub-document or document level.”
Machine Learning and Natural Language Processing in Mental Health: Systematic Review (2021, neutral): “…(PTSD; 3 cases) [47,63,64]; neurodevelopmental disorders (3 cases) [42,58,93]; psychotic spectrum disorders, including schizophrenia (3 cases) [39,95,100]; anxiety (2 cases) [41,98]; personality disorder (1 case) [85]; eating disorders (2 cases) [89,96]; and bipolar disorder (2 cases) [37,102].”