Sleep Disorder Prediction

Predicting Sleep Apnea using AI and Machine Learning

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About This Project

This is a small machine learning project that predicts whether someone has Sleep Apnea based on a few key indicators:

• Stress Level (1-10 scale)
• Sleep Duration (in hours)
• Quality of Sleep (1-10 scale)

We use a Random Forest Classifier in Python, trained on labeled data, achieving roughly 85% accuracy. Users can input their own values to get predictions in real-time.

This project is for educational purposes only. It is not a medical diagnostic tool.

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Features

• Predict Sleep Apnea or Normal sleep status based on user input.
• Interactive command-line interface for real-time predictions.
• Trained using scikit-learn’s Random Forest for robust classification.

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Technologies Used

• Python
• pandas
• scikit-learn

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How to Use

1. Clone the repository

git clone https://github.com/Krish-Patel656/SleepDisorderPrediction.git
cd SleepDisorderPrediction

2. Install dependencies

pip install -r requirements.txt

3. Run the predictor

python predict_sleep_disorder.py