Detection of Sleep Disorders (Insomnia & Sleep Apnea) using RF Algorithm

Sleep plays a vital role in our physical and mental health. Sleep disorders such as Insomnia and Sleep Apnea can be the root cause of serious health issues. Traditional diagnostic methods are time-consuming, which has led researchers to seek new solutions. This project leverages Artificial Intelligence and Machine Learning to find a fast, accurate, and automated way to detect these sleep disorders.|Creaed By:Kosar Tahaei What You Will Learn in This Video: 🔹 Introduction to different types of sleep disorders (Normal, Insomnia, Sleep Apnea) 🔹 Exploring the model's input features (Age, Sleep Duration, Sleep Quality, Physical Activity, Stress Level, Heart Rate, and Daily Steps) 🔹 Data Preprocessing and Feature Engineering steps 🔹 Implementing the Random Forest algorithm in Python (using Pandas and Scikit-learn libraries) 🔹 Comparing Random Forest, KNN, and Logistic Regression algorithms for this medical dataset 🔹 Testing the model with new patient data and generating final predictions