ESC Premium Access

Machine-learning fusion approach for the prediction of atrial fibrillation onset using photoplethysmographic-based smart device

Topic: Artificial Intelligence (Machine Learning, Deep Learning)

Congress Presentation

About the speaker

Doctor Luping Li

Beijing (China)
0 follower

64 more presentations in this session

Comparison of deep learning with traditional models to predict preventable acute care use and spending among heart failure patients

Speaker: Doctor M. Lewis (Tel Aviv, IL)

Thumbnail

Detection of myocardial ischemia by intracoronary ECG using convolutional neural networks

Speaker: Doctor M. Bigler (Bern, CH)

Thumbnail

Home monitoring program for patients following cardiac surgery

Speaker: Mrs M. Sokolskaya (Moscow, RU)

Thumbnail

A new clinical decision support tool based on personalized evidence-based medicine improves outcomes of anticoagulation therapy in patients with atrial fibrillation: an analysis from the AF registry

Speaker: Professor E. Pokushalov (Novosibirsk, RU)

Thumbnail

Early detection of exacerbation of the severe acute respiratory syndrome coronavirus 2 infection using Fitbit (DEXTERITY Pilot Study)

Speaker: Doctor K. Yamagami (Kanazawa, JP)

Thumbnail

Access the full session

e-Cardiology/Digital Health ePosters

Speakers: Doctor L. Li, Doctor M. Lewis, Doctor M. Bigler, Mrs M. Sokolskaya, Professor E. Pokushalov...
Thumbnail

About the event

Image

ESC Congress 2021 - The Digital Experience

27 August - 30 August 2021

Sessions Presentations

ESC 365 is supported by

logo Novo Nordisk
logo Bristol Myers Squibb