Project: Multi-disease prediction app (ML + DL) with a Streamlit dashboard

• 🎯 Goal: Build a Streamlit app that predicts risk for 5 diseases - Heart Disease, Diabetes, Breast Cancer, Chronic Kidney Disease, and Parkinson’s

• 📊 Datasets sourced (public mirrors of the classic Kaggle/UCI sets):

  • Cleveland Heart Disease
  • Pima Indians Diabetes
  • Breast Cancer Wisconsin (Diagnostic)
  • UCI Chronic Kidney Disease
  • UCI Parkinson’s voice dataset

• 🤖 Models trained per disease:

  • Heart → Logistic Regression, Random Forest, XGBoost
  • Diabetes → SVM, KNN, Keras MLP (GPU)
  • Breast Cancer → SVC, Random Forest, Keras ANN (GPU)
  • CKD → Decision Tree, LightGBM
  • Parkinson’s → Random Forest, Keras ANN (GPU)

• 💾 Saved each model with its scaler + feature schema (JSON) so the app can auto-generate input forms per disease

• 🖥️ Next: wire up the 3-page Streamlit app

  • Dashboard - EDA & visual insights per disease
  • Prediction - pick a disease → fill clinical inputs → get risk score
  • About - disease descriptions + illustrations

• ⚙️ Training pipeline uses GPU (TensorFlow/CUDA) for the deep learning models