Ai for autonomous health care on diabetes diagnostics
DOI:
https://doi.org/10.56294/shp2025236Keywords:
diabetes, Artificial Intelligence, Machine Learning, Prediction, Cloud ComputingAbstract
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.
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Copyright (c) 2025 Hari Kiran Vege, Sri Kamal Yandamuri, Jetti Vennela, Sai Venkat (Author)
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