AI-Powered Thermography for Diabetic Foot Risk Stratification: Multicenter Cross-Sectional Study

The TFScan system effectively stratified patients with diabetes into clinically meaningful risk categories, with moderate- and high-risk groups exhibiting a significantly higher burden of vascular, neuropathic, and thermal abnormalities. However, the cross-sectional design, partial reliance on self-report, and low prevalence of advanced complications may limit causal inference. These findings highlight the potential of AI-enhanced thermography to serve as a scalable, objective screening tool for proactive diabetic foot management. Further longitudinal studies are warranted to validate its predictive power and support widespread clinical adoption.