Template-Type: ReDIF-Article 1.0
Title: Ai for autonomous health care on diabetes diagnostics
Author-Name: Kiran Vege, Hari
Author-Name: Yandamuri, Sri Kamal
Author-Name: Vennela, Jetti
Author-Name: Venkat, Sai
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.
Journal: SAP Health and Policy
Year: 2025
DOI: 10.56294/shp2025236
File-URL: https://southam.pub/journals/files/shp/shp2025236en.pdf
File-Format: application/pdf
Handle: RePEc:cwf:shpart:shp2025236