A Machine Learning Approach for Continuous Mining of Nonidentifiable Smartphone Data to Create a Novel Digital Biomarker Detecting Generalized Anxiety Disorder: Prospective Cohort Study.

Choudhary, Soumya; Thomas, Nikita; Alshamrani, Sultan; Srinivasan, Girish; Ellenberger, Janine; Nawaz, Usman; Cohen, Roy

Choudhary, Soumya; Thomas, Nikita; Alshamrani, Sultan; Srinivasan, Girish; Ellenberger, Janine; Nawaz, Usman; Cohen, Roy.

Afiliação

Choudhary S; Department of Research, Behavidence, Inc., New York, NY, United States.
Thomas N; Department of Data Science, Behavidence, Inc., New York, NY, United States.
Alshamrani S; Department of Data Science, Behavidence, Inc., New York, NY, United States.
Srinivasan G; Department of Data Science, Behavidence, Inc., New York, NY, United States.
Ellenberger J; Department of Research, Behavidence, Inc., New York, NY, United States.
Nawaz U; Department of Data Science, Behavidence, Inc., New York, NY, United States.
Cohen R; Department of Research, Behavidence, Inc., New York, NY, United States.

JMIR Med Inform ; 10(8): e38943, 2022 Aug 30.

Article em En | MEDLINE | ID: mdl-36040777

Palavras-chave

algorithm prediction; anxiety; anxiety assessment; behavioral marker; digital marker; digital phenotyping; machine learning; mental health; mining technique; profiling metric; smartphone data

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Idioma: En Revista: JMIR Med Inform Ano de publicação: 2022 Tipo de documento: Article

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