AI in healthcare: Enhancing Diabetic Foot Ulcer Recognition through Deep Learning and Explainable AI

Diabetic foot ulcers (DFU) are prone to getting infected, can lead to hospital stays of several weeks, and in some instances, the person has to undergo leg amputation to stop the infection from going further up the body and becoming a life-threatening issue. This proposed paper develops a Smart Health Care System for recognizing DFU with explainability. The model uses a deep learning architecture called EfficientNet to analyze images of feet so that both ulcerated feet and healthy feet can be correctly identified. It is a system that involves image prediction and symptom data and integrates the two to create a more correct final diagnosis according to the decision-based approach. As per the diagnosis, the system generates AI-based medical prescriptions, which comprise treatment schemes, prescription of medications, diet plans, lifestyle changes, and physical workouts. Moreover, the system creates a detailed PDF medical report which can be shared with the healthcare specialists to be examined further. The proposed system also uses explainable AI (XAI) to address the challenges related to trust and accountability for clinicians and patients.