Multimodal AI Improves Alzheimer Disease Diagnosis Performance

A systematic review published in J Med Internet Res (final search Nov 15, 2025) analyzed 66 studies from 2019–2025 on multimodal AI for Alzheimer disease diagnosis, prognosis, and risk prediction, finding multimodal models consistently outperformed single-modal baselines. Across datasets, ADNI diagnosis averaged 92.5% accuracy, MCI-conversion models averaged AUC 0.922, UK Biobank risk models averaged AUC 0.84, and authors call for standardized benchmarks, transparent evaluation, and clinically grounded designs due to heterogeneity and bias limiting generalizability.