sleep-disorder

A supervised ML classification project that predicts sleep disorders- Insomnia, Sleep Apnea, or None from health and lifestyle features including age, BMI, stress level, sleep duration, and blood pressure, using Logistic Regression, Random Forest, and SVM.

A web-based machine learning app that predicts potential sleep disorders based on health and lifestyle data. Built with Next.js and FastAPI, featuring an interactive UI, real-time predictions, and dark/light mode support.

Predicting sleep disorders using machine learning on patient lifestyle and health data

AI Framework for Sleep Disorder Identification using Ensemble ML models with Django

Full-stack Machine Learning web application for sleep disorder prediction using Flask, Random Forest, SQLite, and Scikit-learn.

Sleep tracking PWA for Non-24-Hour Sleep-Wake Disorder. Actogram visualization, cycle-based logging, offline-first. Built with React + Vite + Supabase.

A Streamlit-based web app for predicting sleep disorders using machine learning.