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Author(s):

Dhinakaran R | Jaikrishnan V | Jaisankar S | Kaviraj M | Dr.R.Madhanmohan
Keywords:

Disease Prediction, Machine Learning, XGBoost, Flask, Healthcare.
Abstract:
This Research Presents A Web-based Disease Prediction System, Deployed On Render, Utilizing Machine Learning To Diagnose Diseases Based On User-reported Symptoms. The System Employs An XGBoost Model, Trained On A Medical Dataset, To Predict Diseases With High Accuracy. Users Interact Through A Flask-powered Web Interface, Input Symptoms, And Receive Predictions Along With Precautionary Measures, Medications, And Dietary Recommendations. The System Is Accessible Online, Making It A Convenient Tool For Preliminary Diagnosis. Future Enhancements Include Real-time Symptom Analysis And Mobile Integration.

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