Prominent Prediction Model for Chronic Diabetes Disease Using Machine Learning

Diabetes is a critical health problem in the twenty- first century that needs special attention and community health care programs. Even among children, diabetes is a condition that is spreading quickly. An elevated blood sugar level is what causes diabetes. A metabolic condition called chronic diabetes mellitus is associated with blood sugar concentrations brought on by either insufficient insulin secretion, resistance to insulin action, or a combination of both. Another type of sickness, primarily affecting the heart, kidneys, blood vessels, nerves, and eyes, is also brought on by diabetes. In order to anticipate medical outcomes, machine learning techniques are applied. Utilizing both historical and current data, machine learning enables constructing models to swiftly assess data and offer outcomes. Providers of health care can make more informed choices about patient diagnoses and treatment alternatives because to machine learning, which enhances health care services as a whole. Performance is assessed using model sensitivity, selectivity, precision, recall, and correctness. Following that, the five top models are chosen to perform assembly. The quality of the dataset is being predicted to be improved by an ensemble model based on boosting. When comparing accuracy, the existing optimization model outperforms the existing single model. A 10-fold cross verification is used to increase the data's resilience.