Revolutionizing personalized medicine using artificial intelligence: a meta-analysis of predictive diagnostics and their impacts on drug development.

ABSTRACT: Artificial intelligence (AI) is transforming the landscape of laboratory medicine by enhancing diagnostic accuracy and enabling more personalized care. Given its growing use in clinical settings, evaluating the performance of AI models in diagnostic tasks is essential to inform evidence-based implementation strategies. This meta-analysis systematically assessed the diagnostic effectiveness of AI-based models. A comprehensive literature search was conducted in PubMed, Scopus, Web of Science, and IEEE Xplore using predefined keywords related to AI and diagnostic accuracy. From 430 retrieved studies, 17 met the inclusion criteria. Data extracted included study design, AI model type, input modality, and performance metrics such as sensitivity, specificity, and area under the curve (AUC). Rando

SUBMITTER: Daemi A 

PROVIDER: S-EPMC12274247 | biostudies-literature | 2025 Jul

REPOSITORIES: biostudies-literature