Potential of machine learning methods in operational risk stratification in patients with coronary artery disease scheduled for coronary bypass surgery

Potential of machine learning methods in operational risk stratification in patients with coronary artery disease scheduled for coronary bypass surgery

Aim. To develop and evaluate the effectiveness of models for predicting mortality after coronary bypass surgery, obtained using machine learning analysis of preoperative data.Material and methods. As part of a cohort study, a retrospective prediction of in-hospital mortality after coronary artery by...

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Bibliographic Details
Main Authors: E. Z. Golukhova, M. A. Keren, T. V. Zavalikhina, N. I. Bulaeva, D. S. Akatov, I. Yu. Sigaev, K. B. Yakhyaeva, D. A. Kolesnikov
Format: Article
Language:Russian
Published: «FIRMA «SILICEA» LLC 2023-03-01
Series:Российский кардиологический журнал
Subjects:
machine learning methods
coronary artery bypass grafting
inhospital mortality after coronary artery bypass grafting
Online Access:https://russjcardiol.elpub.ru/jour/article/view/5211
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