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](https://asset.jmir.pub/assets/1edf201f33e5d4cc9159f4b5374b4df4.png 480w,https://asset.jmir.pub/assets/1edf201f33e5d4cc9159f4b5374b4df4.png 960w,https://asset.jmir.pub/assets/1edf201f33e5d4cc9159f4b5374b4df4.png 1920w,https://asset.jmir.pub/assets/1edf201f33e5d4cc9159f4b5374b4df4.png 2500w)
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- Li N, Feng L, Hu J, Jiang L, Wang J, Han J, Gan L, He Z, Wang G. Using deeply time-series semantics to assess depressive symptoms based on clinical interview speech. Frontiers in Psychiatry 2023;14 View
- Panaite V, Finch D, Pfeiffer P, Cohen N, Alman A, Haun J, Schultz S, Miles S, Belanger H, Kozel F, Rottenberg J, Devendorf A, Barrett B, Luther S. Predictive modeling of initiation and delayed mental health contact for depression. BMC Health Services Research 2024;24(1) View