Augmenting large language models to predict social determinants of mental health in opioid use disorder using patient clinical notes
Integrating the MHCLE model with the HLLIA framework offers an effective approach for predicting SDOMH factors from clinical notes, advancing NLP in OUD care. It highlights the importance of human oversight and sets a benchmark for future research.
Authors
- Mohammad Arif Ul Alam (ORCID: https://orcid.org/0000-0003-1267-1349)
- Inyene E. Essien-Aleksi (ORCID: https://orcid.org/0000-0003-0943-9952)
- Madhavi Pagare (ORCID: https://orcid.org/0000-0002-9669-0725)
- Deva Sai Kumar Bheesetti
Institutions
- University of Massachusetts Lowell (US)
- University of Massachusetts Chan Medical School (US)
- Merrimack College (US)
- National Institute on Aging (US)
Publication Details
- Journal
- JAMIA Open
- Published
- 2025-11-03
- DOI
- https://doi.org/10.1093/jamiaopen/ooaf142
- Primary Topic
- Opioid Use Disorder Treatment
- Type
- article
- Field-Weighted Citation Impact
- 0.00