This book will have a profound impact on the research community by illustrating how machine learning can transform the care of Diabetic Foot Ulcers (DFU). It offers valuable insights into the development and implementation of Decision Support Systems (DSS), which will encourage further research into enhancing machine learning algorithms for DFU prediction, early detection, and personalized treatment strategies. This book aims to bridge the gap between cutting-edge technology and clinical practice, fostering collaboration across disciplines such as computer science, healthcare, and diabetes research. By integrating these fields, this book will facilitate interdisciplinary partnerships that drive innovation in diabetic care. Additionally, policymakers and healthcare administrators will benefit from the insights provided, gaining a better understanding of the potential for machine learning to revolutionize diabetic care pathways. This knowledge could lead to improved patient outcomes and more efficient resource allocation in healthcare systems, ultimately helping to reduce overall costs. The book serves not only as a guide for current advancements but also as a foundation for future research and collaboration, laying the groundwork for a more technology-driven approach to managing diabetic complications.