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RajKhanke
Is there an existing issue for this?
Feature Description
This project aims to predicts whether a person is suffering from the sleep disorder or not and if yes then which disorder like sleep apnea or insomnia based on the Kaggle dataset. The user enters various inputs like age , Occupation , Gender , Sleep Duration , Quality of sleep , Physical activity level , BMI , Blood pressure , Heart rate etc . I will apply four different machine learning models like XGBoost , GBM , logistic regression and Random forest. kaggle data : https://www.kaggle.com/datasets/uom190346a/sleep-health-and-lifestyle-dataset
i will do a complete data analysis ,processing , feature engineering, model training and evaluation and deploy using Streamlit web application
Use Case
Health Monitoring and Diagnosis: This project provides a tool for early detection and diagnosis of sleep disorders. By analyzing lifestyle and health-related inputs, it can help identify whether a person is suffering from sleep apnea, insomnia, or no disorder at all, enabling timely medical intervention.
Personalized Health Recommendations: With insights from the model, users can receive personalized recommendations to improve their sleep quality and overall health. For example, advice on adjusting sleep duration, improving sleep quality, or modifying physical activity levels based on their predicted risk.
Benefits
Early Detection and Prevention: By predicting sleep disorders early, individuals can seek medical advice sooner, potentially preventing more severe health issues associated with untreated sleep disorders.
Enhanced User Engagement: The use of a user-friendly Streamlit web application ensures high user engagement and accessibility, making it easier for individuals to monitor their sleep health and receive actionable insights.
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Priority
High
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