The Value of Extracting Clinician-Recorded Affect for Advancing Clinical Research on Depression: Proof-of-Concept Study Applying Natural Language Processing to Electronic Health Records

BACKGROUND: Affective characteristics are associated with depression severity, course, and prognosis. Patients’ affect captured by clinicians during sessions may provide a rich source of information that more naturally aligns with the depression course and patient-desired depression outcomes. OBJECT...

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Detalles Bibliográficos
Autores principales: Panaite, Vanessa, Devendorf, Andrew R, Finch, Dezon, Bouayad, Lina, Luther, Stephen L, Schultz, Susan K
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2022
Materias:
Original Paper
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9136653/
https://www.ncbi.nlm.nih.gov/pubmed/35551066
http://dx.doi.org/10.2196/34436

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9136653/
https://www.ncbi.nlm.nih.gov/pubmed/35551066
http://dx.doi.org/10.2196/34436

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