Ai for autonomous health care on diabetes diagnostics

Hari Kiran Vege, Sri Kamal Yandamuri, Jetti Vennela and Sai Venkat

South Health and Policy, 2025, vol. 4, 236-236

Abstract: The project aims to improve diabetes prediction using Artificial Intelligence and Machine Learning (AIML) technologies. Diabetes is a chronic disease that needs to be detected early and monitored regularly. Conventional diagnostic methods are based on clinical evaluation and laboratory tests, which are time-consuming and expensive. The system uses cloud computing and machine learning algorithms to create a scalable and effective diabetes prediction model. With patient health data like glucose levels, BMI, age, and insulin levels, the system implements machine learning techniques like Logistic Regression, Random Forest, and Neural Networks to estimate the probability of diabetes. Integration with the cloud provides real-time analytics, data security, and easy access to healthcare professionals.

Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:dbk:southh:2025v4a137

DOI: 10.56294/shp2025236

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