Evaluating predictive performance, validity, and applicability of machine learning models for predicting HIV treatment interruption: a systematic review
Abstract Background HIV treatment interruption remains a significant barrier to achieving global HIV/AIDS control goals. Machine learning (ML) models offer potential for predicting treatment interruption by leveraging large clinical data. Understanding how these models were developed, validated, and...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
BMC
2025-07-01
|
| Series: | BMC Global and Public Health |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s44263-025-00184-4 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|