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June 1, 2016European Heart Journal708 citationsOpen Access

Machine learning for prediction of all-cause mortality in patients with suspected coronary artery disease: a 5-year multicentre prospective registry analysis

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MMManish MotwaniDDDamini DeyDBDaniel S. Berman

Structured PICO

Does machine learning combining clinical and CCTA data improve prediction of 5-year all-cause mortality in patients with suspected coronary artery disease compared to existing clinical or CCTA metrics alone?

P
Population
Patients with suspected coronary artery disease
I
Intervention
Machine learning combining clinical and coronary computed tomography angiography (CCTA) data
C
Comparator
Existing clinical or CCTA metrics alone
O
Outcome
5-year all-cause mortality (ACM)hard clinical

Machine learning models integrating clinical and CCTA data improve 5-year mortality prediction over traditional metrics in patients with suspected CAD.

Abstract

Machine learning combining clinical and CCTA data was found to predict 5-year ACM significantly better than existing clinical or CCTA metrics alone.

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Cite This Study

Motwani et al. (2016) studied this question.

synapsesocial.com/papers/69dd4db727c48be1bb40ccc4https://doi.org/10.1093/eurheartj/ehw188
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