Back

Dynamic prediction of obstructive sleep apnea progression: a deep learning approach using time-varying smartwatch data

29 August 2026 (13:15 - 14:00)
Organised by: Logo
Congress Presentation Part of: Sleep apnoea and the heart Sleep Apnoea ESC2026 Premium Access ESC Congress 2026 European Society of Cardiology

About the speaker

Photo
Professor Yutao Guo

Chinese PLA General Hospital, Beijing (China)

6 More presentations in this session

Presentation thumbnail
Independent and combined effects of DASH diet and sleep quality on hypertension
Doctor S. Zhang (Beijing, CN)
Abstract Slides
Presentation thumbnail
The association between obstructive sleep apnea of varying severity and cardiovascular risk: a systematic review and meta-analysis
Doctor C. Niu (Beijing, CN)
Abstract Slides
Presentation thumbnail
Phenogroup-based stratification of cardiovascular risk in obstructive sleep apnea
Doctor Y. Ou (Boston, US)
Abstract Slides
Presentation thumbnail
Sleep–wake circadian organisation (relative amplitude) and incident cardiovascular disease in UK Biobank
Miss H. Wang (Beijing, CN)
Abstract Slides
Presentation thumbnail
Cardiovascular and inflammatory proteomic signatures distinguish mandibular advancement device from CPAP therapy and predict blood pressure response in obstructive sleep apnea
Doctor Y. Ou (Boston, US)
Abstract Slides

Access the full session

Session thumbnail
Sleep apnoea and the heart

The Event

Event poster

ESC Congress 2026

29 August 2026 13:15 CET
You may be interested in
thumbnail
Congress Presentation
Obstructive sleep apnea assessment using a wearable medical device in patients post-catheter ablation for atrial fibrillation: Validation and predictive value.
12 April 2026
thumbnail
Congress Presentation
Deep learning-based prediction of major arrhythmic events in nonischemic cardiomyopathy
21 May 2023
thumbnail
Congress Presentation
Modeling aortic stenosis progression: impact on follow-up, treatment and survival
29 August 2022
thumbnail
Congress Presentation
From continuous wearable heart rate to fitness forecasting: an interpretable proof-of-concept model to predict change in maximal oxygen uptake
14 April 2026

ESC 365 is supported by

novartis Explore sponsored resources
novo-nordisk Explore sponsored resources

ESC 365 is supported by

novartis Explore sponsored resources
novo-nordisk Explore sponsored resources