Machine learning in psychiatric health records: A gold standard approach to trauma annotation
Abstract Psychiatric electronic health records present unique challenges for machine learning due to their unstructured, complex, and variable nature. This study aimed to create a gold standard dataset by identifying a cohort of patients with psychotic disorders and posttraumatic stress disorder, (P...
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| Main Authors: | Eben Holderness, Bruce Atwood, Marc Verhagen, Ann K. Shinn, Philip Cawkwell, Hudson Cerruti, James Pustejovsky, Mei-Hua Hall |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Publishing Group
2025-08-01
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| Series: | Translational Psychiatry |
| Online Access: | https://doi.org/10.1038/s41398-025-03487-0 |
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