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Machine learning for phenotyping and risk prediction in cardiovascular diseases: a systematic review

Session: New approaches to risk prediction
Topic: Big Data Analysis
Speaker: Professor A. Banerjee (London, GB)
Event: ESC Congress 2019

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Professor Amitava Banerjee

University College London, London (United Kingdom of Great Britain & Northern Ireland)
5 presentations
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6 more presentations in this session

Finding predictors and causes of cardiac surgery ICU readmission using machine learning and causal inference

Speaker: Mr J. Lee (Baltimore, US)

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An evaluation of the use of propensity scores in cardiovascular literature: a systematic review and recommendations

Speaker: Ms J. Rouette (Montreal, CA)

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Balancing risk and benefit in patients with atrial fibrillation: the GARFIELD-AF risk score

Speaker: Professor K. Fox (Edinburgh, GB)

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External validation of the ACEF II operative risk model in a cardiac surgery population: an interim evaluation

Speaker: Doctor M. Georgievska (Skopje, MK)

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Clinical applications of machine learning for prediction of incident atrial fibrillation from the general population: a nationwide cohort study

Speaker: Doctor I. Kim (Seoul, KR)

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New approaches to risk prediction

Speakers: Professor A. Banerjee, Mr J. Lee, Ms J. Rouette, Professor K. Fox, Doctor M. Georgievska...
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ESC Congress 2019

31 August - 4 September 2019

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