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...
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: | |
Online Access: | https://russjcardiol.elpub.ru/jour/article/view/5211 |
Similar Items
-
Subclavian-coronary bypass graft re-operation according to the MICS technique in a patient with angina relapse
by: I. Yu. Sigaev, et al.
Published: (2019-09-01) -
Angiographic Patency of Coronary Artery Bypass Conduits: An Updated Network Meta-Analysis of Randomized Trials
by: Mimi X. Deng, et al.
Published: (2022-09-01) -
“SURGICAL FORMULA” FOR CORONARY BYPASS: NEW OPPORTUNITIES FOR COMPUTER DATA PROCESSING AND PERSONALIZED ASSESSMENT OF TREATMENT RESULTS
by: O.A. MAKHACHEV, et al.
Published: (2024-06-01) -
Angiographic Patency of Coronary Artery Bypass Conduits: A Network Meta‐Analysis of Randomized Trials
by: Mario Gaudino, et al.
Published: (2021-03-01) -
Localization of coronary bypass targets in hard-to-see coronary arteries
by: Rabin Gerrah, et al.
Published: (2023-10-01)