MedTric : A clinically applicable metric for evaluation of multi-label computational diagnostic systems.

ABSTRACT: When judging the quality of a computational system for a pathological screening task, several factors seem to be important, like sensitivity, specificity, accuracy, etc. With machine learning based approaches showing promise in the multi-label paradigm, they are being widely adopted to diagnostics and digital therapeutics. Metrics are usually borrowed from machine learning literature, and the current consensus is to report results on a diverse set of metrics. It is infeasible to compare efficacy of computational systems which have been evaluated on different sets of metrics. From a diagnostic utility standpoint, the current metrics themselves are far from perfect, often biased by prevalence of negative samples or other statistical factors and importantly, they are designed to evaluate gene

SUBMITTER: Saha S 

PROVIDER: S-EPMC10414580 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature