Fuzzy Rule and ML-Based Hybrid Framework for Diabetes Detection

This book introduces a hybrid decision-support system that integrates machine learning fuzzy inference and rule-based logic to improve the early detection of diabetes. Using clinical parameters such as glucose BMI blood pressure insulin and age the model combines statistical learning with expert knowledge to deliver accurate interpretable and reliable predictions. Designed for healthcare professionals researchers and students it demonstrates how intelligent systems can bridge the gap between data-driven analytics and real-world clinical decision-making.