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

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

Session: Allow artificial intelligence to assist with diagnostic heavy lifting

Topic: Artificial Intelligence (Machine Learning, Deep Learning)

Speaker: Ms X. LIU (Beijing, CN)

Event: ESC Congress 2023

Congress Presentation

About the speaker

Ms Xiaofei LIU

Peking University, Beijing (China)

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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)

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)

ECG-based deep learning for detecting epicardial coronary occlusion in acute myocardial infarction

Speaker: Doctor R. Herman (Aalst, BE)

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Allow artificial intelligence to assist with diagnostic heavy lifting

Speakers: Ms X. LIU, Doctor J. Ramirez, Doctor O. Akbilgic, Professor Y. Tamura, Mr D. Sung...

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About the event

ESC Congress 2023

25 August - 28 August 2023

Sessions Presentations

Congress

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

About the speaker

Ms Xiaofei LIU

7 more presentations in this session

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

Electrocardiographic artificial intelligence model for timely detection of preeclampsia

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

Artificial intelligence-assisted examination of cardiac health status through electrocardiogram

ECG-based deep learning for detecting epicardial coronary occlusion in acute myocardial infarction

Access the full session

Allow artificial intelligence to assist with diagnostic heavy lifting

About the event

ESC Congress 2023

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