An Analysis on The Convergence of Artificial Intelligence Techniques in Diabetic Management and Care

Abstract

Diabetes Mellitus(DM) is a lethal and prevalent chronic disease which may lead to multi organ failures in patients. Artificial Intelligence technologies have made prominent progress in diagnosis and management of this chronic disease. AI methods with latest technological development in medical devices, mobile computing and sensor technologies provide better health care services for diabetic management and care. Machine learning and artificial intelligence based automated process for detection and diagnosis of diabetes mellitus is more beneficial than a manual diagnosis. Predictive models derived from the principles of machine learning can be used to develop algorithms for detecting diabetes and managing its consequent complications. These models assist in the self-management of the disease in patients and benefit the health care professionals through clinical decision support. Increase in the number of diabetic cases has resulted in the potential availability of data. Harnessing this data with the application of Artificial Intelligence and ML techniques and algorithms would give a deeper insight into the problems related to the disease and assist in devising comprehensive solutions for the same. This paper aims at analyzing the various AI techniques towards the strategic management of building targeted data driven precision care of the disease.