Artificial intelligence-powered prediction of diabetic complications: from clinical data to molecular omics.

ABSTRACT: Diabetic complications are a major cause of disability and mortality among patients, and early identification of high-risk individuals is essential for precision prevention and management. In recent years, the rapid advancement of artificial intelligence (AI) has provided transformative tools for risk prediction and clinical decision support in diabetes care. In this narrative review, we systematically surveyed studies published between January 2015 and June 2025 in PubMed, Web of Science, and Scopus that applied AI-based predictive modeling for three major diabetic complications: diabetic retinopathy (DR), diabetic nephropathy (DN), and diabetic cardiovascular disease (CVD). A total of 58 studies were included, encompassing models based on clinical features, molecular omics, medical imagi

SUBMITTER: Xie X 

PROVIDER: S-EPMC12936790 | biostudies-literature | 2026 Jan

REPOSITORIES: biostudies-literature