aceMachine learning for estimating and comparing clinical rules for treating diarrheal illness with antibiotics
Acute diarrheal disease is a leading cause of death in children under age 5, disproportionately impacting children in low-resource settings. Although many cases could respond to antibiotic treatment, the benefits of widely prescribing antibiotics must be weighed against the risks of antimicrobial resistance. These challenges motivate development of individualized treatment guidelines for diarrheal disease. In this study, we utilize a framework for creation and evaluation of individualized treatment rules that le…
Individualized treatment rules built with ensemble machine learning can use clinical and diagnostic data to recommend antibiotics while capping the share of children treated, and can quantify what extra biomarkers add.
Evidence
- Peer-reviewedThe International Journal of Biostatistics2026-10-09
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Truvace Impact Record TRV-2026-1680, v1: “Machine learning for estimating and comparing clinical rules for treating diarrheal illness with antibiotics.” Truvace, 2026-10-17. /record/TRV-2026-1680 (accessed at citation time). sha256 1694201de26c8448…
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