Status: Recruiting
Multimodal Deep Learning Model for Predicting the Apnea-Hypopnea Index in Obstructive Sleep
This study aims to develop a multimodal deep learning model that integrates noninvasive signals to predict the severity of obstructive sleep apnea. By establishing a clinically viable and user-friendly monitoring tool, the study seeks to enhance early screening accessibility and support the development of home-based sleep care systems.
Participants needed: 150
Trial details
Age: 30-75Biological sex: AllType: ObservationalSponsor: Fu Jen Catholic UniversityUpdated: Mar 5, 2026Locations: 1
Eligibility criteria
age 30-75 years [+2]
intolerance to the electronic stethoscope or fingertip pulse oximeter [+6]