A Comparative Study of Machine Learning Algorithms for Multi-Disease Healthcare Prediction: A Web-Based Intelligent System

• Madhuri Gokhale

  Author

Machine learning has significantly transformed healthcare analytics, enabling new approaches to early disease detection and clinical decision support. This study presents a web-based platform designed to predict five clinically significant diseases simultaneously: Diabetes, Heart Disease, Lung Cancer, Parkinson’s Disease, and Thyroid Disorders. Disease-specific datasets were sourced from established public repositories and subjected to a systematic preprocessing pipeline encompassing noise removal, normalisation, feature selection, and stratified train-test partitioning. Five supervised machine learning models were confusion matrices and multi-model accuracy comparisons. The platform is designed for scalability, with provisions for integration with electronic health records and wearable health monitoring devices, establishing its suitability as a next-generation clinical decision support tool. The system is intended to function as a decision support aid and does not substitute for professional clinical diagnosis.

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