Development of a machine learning model using 12-lead ECG to improve acute dianosis of pulmonary embolism

Back

ESC Professional Premium Access

Development of a machine learning model using 12-lead ECG to improve acute dianosis of pulmonary embolism

Session: Allow artificial intelligence to assist with diagnostic heavy lifting

Topic: Artificial Intelligence (Machine Learning, Deep Learning)

Speaker: Doctor M. Nobre Menezes (Lisbon, PT)

Event: ESC Congress 2023

Congress Presentation

Add to my library

About the speaker

Doctor Miguel Nobre Menezes

Hospital Lisbon North, Lisbon (Portugal)

1 presentation

0 follower

7 more presentations in this session

Combining hypothesis-driven ECG indices with machine learning improves ventricular arrhythmic risk prediction in a low-risk population

Speaker: Doctor J. Ramirez (Zaragoza, ES)

Electrocardiographic artificial intelligence model for timely detection of preeclampsia

Speaker: Doctor O. Akbilgic (Winston-Salem, US)

Performance of survival neural networks in predicting 10-year cardiovascular disease risk in UK and Chinese populations

Speaker: Ms X. LIU (Beijing, CN)

The exploratory clinical trial of AI-enabled Holter electrocardiogram for diagnosis of paroxysmal atrial fibrillation from sinus rhythm waveforms

Speaker: Professor Y. Tamura (Tokyo, JP)

Artificial intelligence-assisted examination of cardiac health status through electrocardiogram

Speaker: Mr D. Sung (Taipei, TW)

Access the full session

Allow artificial intelligence to assist with diagnostic heavy lifting

Speakers: Doctor M. Nobre Menezes, Doctor J. Ramirez, Doctor O. Akbilgic, Ms X. LIU, Professor Y. Tamura...

Access

About the event

ESC Congress 2023

25 August - 28 August 2023

Sessions Presentations

Congress

ESC 365 is supported by

Explore sponsored resources