https://github.com/mehak-089/healthwise---disease-prediction-system
HealthWise - AI-Powered Disease Prediction A machine learning-based disease prediction system using Streamlit and Random Forest. Enter symptoms to get disease predictions, descriptions, and precautions. 🔹 Features: ✅ Symptom-based disease prediction ✅ Precautionary recommendations ✅ Interactive web interface
https://github.com/mehak-089/healthwise---disease-prediction-system
aiml disease-prediction healthcare-application ml python random-forest streamlit
Last synced: 7 months ago
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HealthWise - AI-Powered Disease Prediction A machine learning-based disease prediction system using Streamlit and Random Forest. Enter symptoms to get disease predictions, descriptions, and precautions. 🔹 Features: ✅ Symptom-based disease prediction ✅ Precautionary recommendations ✅ Interactive web interface
- Host: GitHub
- URL: https://github.com/mehak-089/healthwise---disease-prediction-system
- Owner: Mehak-089
- Created: 2025-03-30T13:11:03.000Z (7 months ago)
- Default Branch: main
- Last Pushed: 2025-03-30T13:24:52.000Z (7 months ago)
- Last Synced: 2025-03-30T14:22:44.546Z (7 months ago)
- Topics: aiml, disease-prediction, healthcare-application, ml, python, random-forest, streamlit
- Language: Python
- Homepage:
- Size: 2.1 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# HealthWise - Disease Prediction System
## Overview
HealthWise is a machine learning-based disease prediction system that allows users to input symptoms and receive predictions about possible diseases. It provides symptom descriptions and recommended precautions to help users take appropriate action.
## Features
- Predicts diseases based on user-input symptoms.
- Provides a detailed description of predicted diseases.
- Suggests precautions for the predicted diseases.
- Uses a trained Random Forest model for predictions.
- Built using **Streamlit** for an interactive and user-friendly web interface.
## Installation & Setup
### Prerequisites
Ensure you have Python installed along with the required libraries:
```bash
pip install -r requirements.txt
```
### Running the Application
1. Clone the repository:
```bash
git clone
cd HealthWise
```
2. Install dependencies:
```bash
pip install -r requirements.txt
```
3. Create and copy `config.toml` file into your device's Streamlit folder to ensure smooth execution.
4. Run the Streamlit app:
```bash
streamlit run app.py
```
## File Structure
```
HealthWise/
│-- app.py # Main application file
│-- train_model.py # Script to train the ML model
│-- dataset.csv # Dataset used for training
│-- disease_prediction_model.pkl # Pretrained model
│-- pages/ # Additional Streamlit pages
│-- .devcontainer/ # DevContainer configuration
│-- symptom_Description.csv # Descriptions of symptoms
│-- symptom_precaution.csv # Precautionary measures for diseases
│-- Symptom-severity.csv # Severity levels of symptoms
│-- requirements.txt # Dependencies for the project
```
## Model Details
- The disease prediction model is built using **Random Forest**.
- The model is trained using labeled symptom data from `dataset.csv`.
- The trained model is saved as `disease_prediction_model.pkl`.