Using Machine Learning to Assess Factors Associated With North American Pharmacist Licensure Examination Performance
ML algorithms accurately classified students' NAPLEX first-time performance in this cohort and could offer notable improvements to existing strategies colleges use to identify potentially at-risk students.
Authors
- Jeffery Talbert (ORCID: https://orcid.org/0000-0002-4304-5167)
- Clark D. Kebodeaux (ORCID: https://orcid.org/0000-0003-1217-9848)
- Frank Romanelli (ORCID: https://orcid.org/0000-0002-3792-7390)
- Douglas R. Oyler (ORCID: https://orcid.org/0000-0002-6153-831X)
- Esther P. Black (ORCID: https://orcid.org/0000-0003-2350-7536)
- Hope H. Brandon (ORCID: https://orcid.org/0000-0002-1509-7381)
Institutions
- University of Kentucky (US)
Publication Details
- Journal
- American Journal of Pharmaceutical Education
- Published
- 2025-10-15
- DOI
- https://doi.org/10.1016/j.ajpe.2025.101885
- Primary Topic
- Innovations in Medical Education
- Type
- article
- Field-Weighted Citation Impact
- 0.00