DIABETES PREDICTION AND ANALYSIS FOR AI POWERED ECOSYSTEM

Abstract

The global burden of diabetes necessitates the development of advanced methods for both early prediction and comprehensive analysis. Characterized by high blood glucose levels, Diabetes mellitus is a rapidly growing chronic disease affecting millions of people worldwide. Its effective diagnosis, prediction, and management are crucial for preventing serious health complications such as hypo- and hyperglycemia. In this paper, we present an integrated framework for an ecosystem designed to address these challenges. 
The methodology, informed by academic literature from 2020 to 2024, focuses on identifying high-risk individuals through the analysis of key demographic, lifestyle, and historical health data. A comprehensive study of diabetes diagnosis was done using data analysis and prediction technique. Moreover, it facilitates the development of more optimized solutions. This work contributes a model for grassroots-level health surveillance and risk assessment, demonstrating that valuable public health insights can be gained without relying on a complex technological infrastructure.