ECGWiz: a unified and generalizable AI model for comprehensive ECG diagnosis

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ECGWiz: a unified and generalizable AI model for comprehensive ECG diagnosis

Session: Innovations in cardiac health prediction: integrating deep learning with multimodal data analysis

Topic: Electrocardiogram (ECG) and Arrhythmia Analysis

Speaker: Mr I. Vatsaraj (Baltimore, US)

Event: ESC Congress 2024

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Mr Ishan Vatsaraj

Baltimore (United States of America)

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5 more presentations in this session

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Detection and risk stratification of cardiac amyloidosis patients by integration of imaging and non-imaging data using a machine learning approach

Speaker: Doctor C. Spielvogel (Vienna, AT)

Standardization of transthoracic impedance values for estimating heart failure and its utility

Speaker: Doctor D. Nose (Fukuoka, JP)

Machine learning for prediction of incident heart failure and heart failure hospitalisation: multi-cohort development, validation and association with clinical phenotypes

Speaker: Associate Professor Y. Nakao (Kyoto, JP)

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Innovations in cardiac health prediction: integrating deep learning with multimodal data analysis

Speakers: Mr I. Vatsaraj, Associate Professor K. Lee, Doctor G. Siontis, Doctor C. Spielvogel, Doctor D. Nose...

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ESC Congress 2024

30 August - 2 September 2024

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