ESC 365 - Machine-learning based prediction of obstructive coronary artery disease using integrated submodules of clinical information, chest x-ray, and electrocardiography

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Machine-learning based prediction of obstructive coronary artery disease using integrated submodules of clinical information, chest x-ray, and electrocardiography

Session: Non-invasive methods for evaluating coronary artery disease

Topic: Noninvasive Diagnostic Methods

Speaker: Professor R. Heo (Seoul, KR)

Event: ESC Congress 2024

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Professor Ran Heo

Hanyang university medical center, Seoul (Korea (Republic of))

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7 more presentations in this session

Non-invasive imaging to guide percutaneous coronary revascularization in chronic total occlusion: a systematic review and meta-analysis

Speaker: Doctor G. Bisaccia (Chieti, IT)

Enhancing computational fluid dynamics simulation for coronary artery disease analysis through spatial iterative modeling

Speaker: Mr M. Arya (Izmir, TR)

Quantitative myocardial blood flow distribution derived from CCTA and determination of myocardium at risk in the FAST TRACK CABG trial

Speaker: Professor P. Serruys (Galway, IE)

Prognostic implication of computational angiography-derived fractional flow reserve in patients with non-obstructive coronary artery disease

Speaker: Mr Y. Hung (Hong Kong, HK)

angioPy: an open-source, deep learning-driven tool for coronary artery segmentation

Speaker: Doctor T. Mahendiran (Aalst, BE)

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Non-invasive methods for evaluating coronary artery disease

Speakers: Professor R. Heo, Doctor G. Bisaccia, Mr M. Arya, Professor P. Serruys, Mr Y. Hung...

About the event

ESC Congress 2024

30 August - 2 September 2024

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