Using Machine Learning to Predict Medication Therapy Problems among Patients with Chronic Kidney Disease
In outpatient primary care, a machine learning-based MTP risk calculator that uses routinely available clinical data can identify patients with moderate-high-risk CKD who are at high risk for developing MTPs.
Authors
- Melanie R. Weltman (ORCID: https://orcid.org/0000-0003-2232-0454)
- Linda-Marie U. Lavenburg
- Manisha Jhamb (ORCID: https://orcid.org/0000-0002-9178-1468)
- Zhuoheng Han (ORCID: https://orcid.org/0009-0006-9506-9837)
- Jonathan G. Yabes (ORCID: https://orcid.org/0000-0002-9406-2362)
- Thomas D. Nolin (ORCID: https://orcid.org/0000-0003-4339-1382)
- Alaa A. Alghwiri (ORCID: https://orcid.org/0009-0006-4815-5652)
- Yi‐Fan Chen (ORCID: https://orcid.org/0009-0007-8595-1380)
Institutions
- University of Pittsburgh (US)
- University of Pittsburgh Medical Center (US)
Publication Details
- Journal
- American Journal of Nephrology
- Published
- 2025-06-17
- DOI
- https://doi.org/10.1159/000546540
- Citations
- 2
- Primary Topic
- Medication Adherence and Compliance
- Type
- article
- Field-Weighted Citation Impact
- 3.03