دراسة استقصائية حول نماذج التنبؤ بمرض القدم السكرية القائمة على الذكاء الصنعي وطرق معالجة الصور

Abstract

Machine learning plays a dominant role in many aspects of health care, from diagnosis to treatment and even to epidemiology. Until very recently, medicine relied solely on the professional expertise of physicians. But with the growth in the size of databases, the applications of artificial intelligence became more present, and the benefits of applying machine learning in medicine became more and more famous.

Diabetes is one of the very common diseases and has taken an important place in medicine. It is a metabolic disease where improper management of blood glucose level leads to the risk of many diseases like foot diseases, ulcers, amputations, etc.

Diabetic foot ulcers and amputation are major morbidity. Prevention of diabetic foot can be achieved by identifying patients at risk and putting in place preventive measures.

There has been a great deal of research involving computer and technology methods for detecting and identifying diabetic foot ulcers, but there is a lack of systematic comparisons of state-of-the-art technology.

In this research, we will present several studies conducted for the early detection of diabetic foot using image processing and machine learning, compare the results, discover the problems of each research, and finally suggest some methods and solutions for the early detection of diabetic foot.