Integrating Regenerative Therapies and Artificial Intelligence for Precision Management of Diabetic Foot Ulcers

Diabetic foot ulcers (DFUs) represent one of the most devastating complications of diabetes, leading to high rates of amputation and mortality. Their multifactorial pathogenesis-including neuropathy, ischemia, infection, and immune dysfunction-creates a chronic inflammatory microenvironment that impairs tissue repair and regeneration.

Emerging regenerative strategies using stem cells and extracellular vesicles (EVs) have demonstrated potential to restore vascularization and modulate inflammation. In particular, miRNA-enriched EVs regulate key wound-healing pathways such as angiogenesis, extracellular matrix remodeling, and oxidative stress response. Meanwhile, small-molecule drugs targeting hypoxia and inflammatory cascades are being explored to enhance re-epithelialization and fibroblast migration. Parallel advances in artificial intelligence (AI) and optical sensing-using visible, infrared, or hyperspectral imaging-enable automated wound detection, tissue classification, and healing prediction with high accuracy.

Despite these developments, translation remains limited by unstable therapeutic efficacy, variable biomarker expression, and the absence of standardized evaluation systems. AI-based wound assessment requires robust datasets and clinical validation to ensure reliability across diverse populations.

Integrating molecular-targeted therapies with AI-assisted diagnostic platforms could establish a next-generation DFU management framework-combining precise molecular intervention, automated wound monitoring, and personalized treatment planning-to achieve reliable, real-time, and patient-centered wound care.