Artificial Intelligence and Machine Learning in Diabetic Foot Ulcer Care: Advances in Diagnosis, Treatment, Prognosis, and Novel Therapeutic Strategies

Despite promising advances, several challenges impede clinical translation, including data standardization, model explainability, regulatory compliance, clinical workflow integration, prospective validation, and equitable implementation. Collaborative efforts among clinicians, data scientists, regulators, and patients are essential to translate AI-driven innovations into routine DFU management, potentially reducing amputations and improving outcomes for this global health burden.