Artificial Intelligence and Machine Learning Techniques for Diabetes Healthcare: A Review

Abstract

All aspects of our lives, including healthcare, are being reshaped by AI/ML (artificial intelligence/machine learning). Diabetic treatment might benefit greatly from the use of AI and ML, which could make it more effective and less time-consuming. In terms of data availability, the large number of diabetics in India brings a unique set of challenges, but it also gives an opportunity. With the use of electronic medical records, India may become a world leader in this field. The use of AI/ML might shed light on our issues and help us come up with solutions that are unique to each.

In this study paper we have to study the techniques for diabetes care using artificial intelligence and machine learning. Through a combination of qualitative and quantitative research methods, this paper analyzes types of Diabetes Mellitus (DM) diagnosis. It is help in treatment to avoid complications and minimize the risk of major health issues. There are benefits and cons to each ML and AI method. As a consequence, methods for the automatic identification of DM have been developed using both techniques. To perform like a human, AI and ML-based strategies need cast ability and explain ability since many of the best-performing Ml and AI technologies are the least transparent.

In conclusion Based on the findings of the evaluation of literature and the current research, artificial intelligence and machine learning techniques have practically limitless uses in the healthcare sector. AI and machine learning are now being used to assist hospitals streamline administrative procedures, customize medical care, and cure infectious illnesses. Data science research has the potential to enhance diabetes mellitus diagnosis and diabetes type prediction, which is beneficial to both medical practitioners and patients. The process of developing a machine learning-based model for diabetes detection saves time.