This paper is in the following e-collection/theme issue:

Formative Evaluation of Digital Health Interventions (1152) Natural Language Processing (410) Electronic Health Records (665) Depression and Mood Disorders; Suicide Prevention (916) Clinical Information and Decision Making (729)

Published on in Vol 6, No 5 (2022): May

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/34436, first published .
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

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

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

Authors of this article:

Vanessa Panaite 1, 2 Author Orcid Image ;   Andrew R Devendorf 1, 2 Author Orcid Image ;   Dezon Finch 2 Author Orcid Image ;   Lina Bouayad 3 Author Orcid Image ;   Stephen L Luther 2, 4 Author Orcid Image ;   Susan K Schultz 5, 6 Author Orcid Image
Article Authors Cited by Tweetations (5) Metrics
Vanessa Panaite 1, 2, PhD;  Andrew R Devendorf 1, 2, MA;  Dezon Finch 2, PhD;  Lina Bouayad 3, PhD;  Stephen L Luther 2, 4, PhD;  Susan K Schultz 5, 6, MD

1 Department of Psychology, University of South Florida , Tampa, FL, US

2 Research Service, James A. Haley Veterans' Hospital , Tampa, FL, US

3 Department of Information Systems and Business Analytics, Florida International University , Miami, FL, US

4 College of Public Health, University of South Florida , Tampa, FL, US

5 Mental Health and Behavioral Sciences, James A. Haley Veterans' Hospital , Tampa, FL, US

6 Department of Psychiatry and Behavioral Neurosciences, University of South Florida , Tampa, FL, US

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