Clinical Trial

Multimodal Deep Learning Model for Predicting the Apnea-Hypopnea Index in Obstructive Sleep

Recruiting
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Record status
This record was last updated March 5, 2026 (before its estimated July 31, 2026 completion). Its status may not reflect the trial's current state.
Summary
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.
Protocol Amendment History 1 amendment
This ClinicalTrials.gov record has been amended once since 2026-02-26.
Trial Details
NCT Number NCT07447999
Lead Sponsor Fu Jen Catholic University
Conditions Obstructive Sleep Apnea (OSA), Polysomnography
Enrollment 150 participants
Start Date 2025-09-05
Primary Completion 2026-07-31 (estimated)
Study Completion 2026-07-31 (estimated)
Updated on ClinicalTrials.gov 2026-03-05