Abstract

ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT: EMERGING APPLICATIONS, CLINICAL OPPORTUNITIES AND CHALLENGES

Sachin Kumar, Vijay Vaishnav, Surabhi Raviprakash Singh*

ABSTRACT

Diabetes mellitus is a serious chronic metabolic disease marked by continuous problems in the regulation of glucose and is linked to a wide range of cardiovascular, renal, neurological, ophthalmic and other complications. Because of the growing number of people with diabetes, the difficulty of providing individualized treatment and the large amount of health data that is produced as part of routine care, there is a growing need for more intelligent methods of managing the disease. Artificial intelligence (AI), which encompasses machine learning, deep learning, natural language processing and predictive analytics, is becoming increasingly the subject of investigation as a means of improving diabetes prevention, screening, diagnosis, monitoring, treatment selection and the management of complications. These AI systems are able to combine data from continuous glucose monitors, electronic health records, laboratory tests, medication records, dietary information, physical activity, wearable sensors and medical images in order to detect patterns that are hard to spot using traditional methods. The applications involve the prediction of diabetes risk, forecasting glucose levels, the detection of both hypoglycemia and hyperglycemia, automated insulin delivery, the giving of individualized treatment recommendations, screening for diabetic retinopathy, the identification of the risk of diabetic kidney disease and digital assistance in making lifestyle changes. AI can also help healthcare professionals by decreasing the amount of information they have to deal with and allowing for more personalized decisions. Yet problems relating to data quality, algorithmic bias, explainability, privacy, cybersecurity, interoperability, regulatory supervision, cost and unequal access still constitute significant obstacles. AI should thus be seen as a decision-support tool and not as a substitute that can operate autonomously for healthcare professionals. This review looks at the principles, major applications, benefits, limitations, ethical issues and future possibilities of the use of AI in the management of diabetes, with a special focus on its potential role in achieving precision and patient-centred diabetes care.

Keywords: Artificial intelligence, diabetes mellitus, machine learning, deep learning, continuous glucose monitoring, precision medicine, diabetic retinopathy, glucose prediction, digital health, automated insulin delivery.