Predicting the Risk of Sleep Disorders Using a Machine Learning-Based Simple Questionnaire: Development and Validation Study.

Seokmin Ha Su Jung Choi Sujin Lee Reinatt Hansel Wijaya Jee Hyun Kim Eun Yeon Joo Jae Kyoung Kim

Published in: Journal of medical Internet research (2023)

SLEEPS has the potential to improve the diagnosis and treatment of sleep disorders by providing more accessibility and convenience. The creation of a publicly accessible website based on the algorithm provides a user-friendly tool for assessing the risk of OSA, COMISA, and insomnia.

Keyphrases

machine learning
sleep quality
physical activity
obstructive sleep apnea
deep learning
artificial intelligence
big data
depressive symptoms
human health
low cost
positive airway pressure