Enhancing Diabetes Mellitus Prediction with Machine Learning Techniques
Authors:- Mrs. S. Sangeetha, P Kowsika, M Swathihasree, K.Shalini, K.Kokila Lakshmi
Abstract- Diabetes is a chronic metabolic condition that affects millions of individuals globally and can have serious long-term health effects if left untreated. Diabetes is a fast growing worldwide health issue that needs to be identified early and managed well to avoid serious consequences. Conventional diagnosis techniques depend on intrusive blood testing and clinical assessments, which can be costly, time-consuming, and unavailable to many. In order to identify at-risk individuals in a non-invasive, economical, and real-time manner, this project intends to create an AI-driven diabetes prediction system utilizing machine learning techniques. The technology improves patient outcomes and lowers the risk of complications by utilizing predictive algorithms to enable early diagnosis. Due to a lack of early symptoms or restricted access to medical facilities, many people go untreated. By providing automated, data-driven predictions that help patients and medical professionals assess risk, machine learning algorithms can close this gap. This device can revolutionize diabetes screening and enable people to take preventative action before the disease progresses.
