Intelligent Sleep Disorder Predictor and Personalized Wellness Guide Using Enhanced Machine Learning

Sleep disorders are increasingly becoming a known risk factor to global health and overall quality of life. In the paper, an intelligent system is described that utilizes a Random Forest Classifier trained on 15 demographic, physiological, lifestyle, and behavioral attributes to predict Sleep Apnea and Insomnia. Integrated within a Flask web application, the system has two functions: It provides an immediate risk prediction based on input health parameters from the user, and it has a chatbot that provides individual lifestyle health recommendations, treatments, and specialist referrals. The proposed system has the potential to offer a costeffective, early sleep disorder screening assessment, and can be used both as a stand-a-lone system as well as starting point before meeting with a sleep specialist. It highlights the potential of integrating machine learning with actionable health recommendations.