• Vedant Sase
• Prof.Ravi Chaudhari
• Vaishnav Sase
• kundan Sriteja
• Vedant Deshpande

This project presents a machine learning-based system for the early detection of multiple diseases, including diabetes, heart disease, and kidney disease. By analyzing patient input data such as symptoms and clinical measurements, the system predicts the likelihood of various health conditions using classification algorithms. The goal is to support early diagnosis and assist healthcare professionals by providing quick, accurate, and cost-effective predictions. The proposed model demonstrates strong performance and offers a foundation for scalable, AI-driven healthcare applications.

Multiple Disease Detection Disease Prediction System Machine Learning in Healthcare Medical Diagnosis Classification Algorithms AI in Health Symptom-Based Diagnosis Predictive Analytics Diabetes Prediction Heart Disease Detection Kidney Disease Prediction Multi-label Classification Healthcare Decision Support Early Diagnosis Health Data Analysis

"Hybrid Framework For Multiple Disease", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 5, page no.i379-i382, May-2025, Available :http://www.jetir.org/papers/JETIR2505942.pdf

"Hybrid Framework For Multiple Disease", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 5, page no. ppi379-i382, May-2025, Available at : http://www.jetir.org/papers/JETIR2505942.pdf