Availability of evidence for predictive machine learning algorithms in primary care: a systematic review

Abstract

Question Which machine learning (ML) predictive algorithms have been implemented in primary care, and what evidence is publicly available for supporting their quality?

Findings In this systematic review of 43 predictive ML algorithms in primary care from scientific literature and the registration databases of the US Food and Drug Administration and Conformité Européene, there was limited publicly available evidence across all artificial intelligence life cycle phases from development to implementation. While the development phase (phase 2) was most frequently reported, most predictive ML algorithms did not meet half of the predefined requirements of the Dutch artificial intelligence predictive algorithm guideline.

Meaning Findings of this study underscore the urgent need to facilitate transparent and consistent reporting of the quality criteria in literature, which could build trust among end users and facilitate large-scale implementation.