ESC 365 - How does lead selection impact diagnosis through AI? Implications for continuous monitoring systems using convolutional neural networks

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How does lead selection impact diagnosis through AI? Implications for continuous monitoring systems using convolutional neural networks

Session: Artificial intelligence innovations in cardiac risk assessment and disease prediction

Topic: Artificial Intelligence (Machine Learning, Deep Learning)

Speaker: Professor J. Millet (Valencia, ES)

Event: ESC Congress 2024

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About the speaker

Professor Jose Millet

Universitat Politecnica de Valencia, Valencia (Spain)

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6 more presentations in this session

The added value of device measured physical activity to the prediction of incident cardiovascular disease.

Speaker: Mr A. Sturge (Oxford, GB)

Prospective evaluation of an AI algorithm for real-time LVEF assessment in acute coronary syndrome using left coronary angiograms: the CathEF multicenter study

Speaker: Doctor R. Avram (Montreal, CA)

Machine learning model using heart rate variability for the prediction of vasovagal syncope

Speaker: Mr J. Cho (Seoul, KR)

Artificial intelligence in cardiology: a machine learning model for supraventricular tachycardia discrimination

Speaker: Doctor P. Avila Alonso (Madrid, ES)

Deep learning enables the fully automated quantification of high-resolution cardiac CT images: human in loop for model development

Speaker: Mr G. Baj (IT)

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Artificial intelligence innovations in cardiac risk assessment and disease prediction

Speakers: Professor J. Millet, Mr A. Sturge, Doctor R. Avram, Mr J. Cho, Doctor P. Avila Alonso...

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ESC Congress 2024

30 August - 2 September 2024

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