Long-term clinical outcomes informed by artificial intelligence-enabled single-lead ECG detection of reduced ejection fraction

Back

ESC Professional Premium Access

Long-term clinical outcomes informed by artificial intelligence-enabled single-lead ECG detection of reduced ejection fraction

Session: Machine-learning approaches for the diagnosis of heart failure

Topic: Epidemiology, Prognosis, Outcome

Speaker: Mr A. Alrumayh (London, GB)

Event: ESC Congress 2024

Congress Presentation

Add to my library

About the speaker

Mr Abdullah Alrumayh

London (United Kingdom of Great Britain & Northern Ireland)

0 follower

7 more presentations in this session

Accurate detection of dilated cardiomyopathy onset through machine learning predictions from ECG data

Speaker: Doctor E. Sieliwonczyk (Antwerpen, BE)

Machine learning methods for diagnostic disease prediction and treatment decisions in parvovirus B19 positive viral cardiomyopathy

Speaker: Doctor C. Baumeier (Berlin, DE)

Construction of an inflammatory, nutritional, and metabolic prognostic risk score in patients with heart failure with preserved ejection fraction: a machine learning-based approach

Speaker: Doctor J. Feng (Beijing, CN)

Artificial intelligence to detect pulmonary congestion on chest computed tomography in consecutive dyspnoeic patients

Speaker: Professor O. Nielsen (Copenhagen, DK)

Diagnostic and prognostic evaluation of an echocardiography-based artificial intelligence algorithm for detecting HFpEF: a case-control analysis

Speaker: Assistant Professor A. Chandra (Dallas, US)

Access the full session

Machine-learning approaches for the diagnosis of heart failure

Speakers: Mr A. Alrumayh, Doctor E. Sieliwonczyk, Doctor C. Baumeier, Doctor J. Feng, Professor O. Nielsen...

Access

About the event

ESC Congress 2024

30 August - 2 September 2024

Sessions Presentations

Congress

ESC 365 is supported by

Explore sponsored resources