Condition: Obstructive Sleep Apnea (OSA) · Polysomnography · Sponsor: Fu Jen Catholic University
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.
This description comes directly from the study's public registry record.
Ke-Yun Chao, PhD · +886-905-301-879 · C00152@mail.fjuh.fju.edu.tw
Always discuss trial participation with your own doctor first.
| Fu Jen Catholic University Hospital, Fu Jen Catholic University | New Taipei City, Taiwan | Recruiting |
Get one email when the public record changes — results posted, or the study's status changes. Nothing else, ever.
We email about this public record only. Unsubscribe anytime with one click. Never medical advice.
This page is independently generated by Eichor from the public ClinicalTrials.gov record and re-synced daily. It is not the sponsor's official website unless claimed. Nothing here is medical advice; eligibility is always determined by the study team — talk to your own doctor first.
Source record: clinicaltrials.gov/study/NCT07447999