{"id":29092250,"url":"https://github.com/ruchit0807/heart_disease_prediction","last_synced_at":"2026-05-04T12:31:15.866Z","repository":{"id":300545272,"uuid":"1006440389","full_name":"Ruchit0807/HEART_DISEASE_PREDICTION","owner":"Ruchit0807","description":"An interactive ML-powered web app that predicts the risk of heart disease based on clinical inputs like age, chest pain, cholesterol, ECG, and more. 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Powered by machine learning, it offers an accessible tool for early risk assessment—just by entering a few health metrics.\n\n🚀 What It Does\nThe app analyzes user input across several medically significant features to estimate the risk of heart disease. These inputs include:\n\n🧓 Age\n\n🚻 Sex\n\n❤️ Chest Pain Type\n\n🩺 Resting Blood Pressure (mm Hg)\n\n🧪 Serum Cholesterol (mg/dl)\n\n🍬 Fasting Blood Sugar \u003e 120 mg/dl\n\n🧠 Resting ECG Results\n\n🏃 Maximum Heart Rate Achieved\n\n🏋️ Exercise-Induced Angina\n\n📈 Slope of ST Segment\n\n## 🧠 Behind the Scenes\nThis app uses a trained machine learning model (KNN, Logistic Regression, etc.) on the Cleveland Heart Disease dataset to make predictions. It processes the provided inputs through a pre-fitted scaler and outputs the probability of heart disease risk in real-time.\n\n\n## 👤 Who’s It For?\nAnyone curious about their cardiovascular health! While not a replacement for a real diagnosis, it’s a helpful early warning tool for awareness and prevention.\n\n\n## 💡 Technologies Used\n🐍 Python\n📊 scikit-learn, pandas\n🌐 Streamlit (for UI)\n💾 Joblib (for model deployment)\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fruchit0807%2Fheart_disease_prediction","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fruchit0807%2Fheart_disease_prediction","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fruchit0807%2Fheart_disease_prediction/lists"}