🌡️ Medical Disease Prediction API

📌 Description

This API predicts diseases based on symptoms provided by the user. It utilizes a Random Forest machine learning model trained on a medical dataset and returns:

• 🏥 A predicted disease
• 📊 A confidence score
• 📖 A detailed description
• ✅ Recommended precautions

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🚀 Technologies Used

🔹 Python
🔹 Flask
🔹 Pandas
🔹 NumPy
🔹 Joblib
🔹 Matplotlib
🔹 Seaborn
🔹 Scikit-learn (Random Forest Classifier, Model Selection, Metrics)

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📊 Model Performance

Our Random Forest model was trained and evaluated using cross-validation. Here are the key performance metrics:

• 🎯 Accuracy: 99.08%
• 📈 Precision: 99.00%
• 🔄 Recall: 99.00%
• 📉 F1-score: 98.94%

🔢 Confusion Matrix

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🛠️ Installation

1️⃣ Clone the repository

git clone https://github.com/Oussamaroom67/modelApiPredictApp.git
cd modelApiPredictApp

2️⃣ Install dependencies

pip install -r requirements.txt

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🎯 Usage

▶️ Start the API

python api.py

📌 The API will run on: http://127.0.0.1:5000/

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🔗 Available Endpoint

🔥 POST /predict

• Description: Predicts a disease based on symptoms.
• Request Body (JSON):

  {
    "symptoms": ["fatigue", "fever", "cough"]
  }

• Response Example (JSON):

  {
    "disease": "Influenza",
    "confidence": 0.87,
    "description": "Influenza is a viral infection that attacks the respiratory system...",
    "precautions": ["Drink plenty of water", "Get rest", "Consult a doctor"]
  }

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📜 License

This project is licensed under the MIT License.

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👤 Authors

📝 Project developed by Oussama Nouhar, Omaima Siaf, and Souhayla Ghanem.