An Explainable AI-Enabled Framework for the Diabetes Classification

Abstract

Nowadays, Diabetes has become a prominent health issue that spans several categories determined by characteristics such as clinical presentation, disease progression, and pathophysiology. A real-time monitoring and management system is necessary to mitigate this life-threatening disease and safeguard individuals. The potential of Artificial Intelligence (AI) to change the management of Diabetes and enhance outcomes for persons with the condition is substantial. While AI shows promise in its ability to forecast Diabetes, it also presents a challenge due to its black-box nature. To address this concern, a proposed framework incorporating explainable AI is suggested for classifying Diabetes. This framework serves to elucidate the decisions made by the AI model. Furthermore, it was assessed using three distinct datasets categorized according to Diabetes categorization. Understanding the decision-making process of AI in the medical field fosters trust between healthcare providers and patients.

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