Multimodal Assessment of Schizophrenia and Depression Utilizing Video, Acoustic, Locomotor, Electroencephalographic, and Heart Rate Technology: Protocol for an Observational Study.

Cotes, Robert O; Boazak, Mina; Griner, Emily; Jiang, Zifan; Kim, Bona; Bremer, Whitney; Seyedi, Salman; Bahrami Rad, Ali; Clifford, Gari D

Cotes, Robert O; Boazak, Mina; Griner, Emily; Jiang, Zifan; Kim, Bona; Bremer, Whitney; Seyedi, Salman; Bahrami Rad, Ali; Clifford, Gari D.

Afiliação

Cotes RO; Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA, United States.
Boazak M; Animo Sano Psychiatry, Durham, NC, United States.
Griner E; Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA, United States.
Jiang Z; Department of Biomedical Informatics, Emory University School of Medicine, Atlanta, GA, United States.
Kim B; Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA, United States.
Bremer W; Visual Medical Education, Emory School of Medicine, Atlanta, GA, United States.
Seyedi S; Department of Biomedical Informatics, Emory University School of Medicine, Atlanta, GA, United States.
Bahrami Rad A; Department of Biomedical Informatics, Emory University School of Medicine, Atlanta, GA, United States.
Clifford GD; Department of Biomedical Informatics, Emory University School of Medicine, Atlanta, GA, United States.

JMIR Res Protoc ; 11(7): e36417, 2022 Jul 13.

Article em En | MEDLINE | ID: mdl-35830230

Palavras-chave

acoustic; biomarker; computer vision; depression; digital biomarker; heart rate; machine learning; multimodal; schizophrenia; technology

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Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Guideline / Observational_studies / Prognostic_studies / Qualitative_research Idioma: En Ano de publicação: 2022 Tipo de documento: Article

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