Derivation and external validation of mass spectrometry-based proteomic model using machine learning algorithms to predict plaque rupture in patients with acute coronary syndrome-Reference-Cited by-同舟云学术

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Derivation and external validation of mass spectrometry-based proteomic model using machine learning algorithms to predict plaque rupture in patients with acute coronary syndrome

Published:2024-09 Issue: Volume:563 Page:119904
ISSN:0009-8981
Container-title:Clinica Chimica Acta
language:en
Short-container-title:Clinica Chimica Acta

Author:

Wu Jianing,Ma Ke,Ma Jie,Li Yulin,Ren Yongkui

Funder

National Natural Science Foundation of China

Beijing Municipal Administration of Hospitals Clinical Medicine Development of Special Funding Support

National Natural Science Foundation of China-Shenzhen Robotics Research Center Project

Publisher

Elsevier BV

Reference45 articles.

1. Global, Regional, and National Burden of cardiovascular diseases for 10 causes, 1990 to 2015;Roth;J. Am. Coll. Cardiol.,2017

2. Global burden of cardiovascular diseases and risk factors, 1990–2019: update from the GBD 2019 study;Roth;J. Am. Coll. Cardiol.,2020

3. Plaque rupture and intact fibrous cap assessed by optical coherence tomography portend different outcomes in patients with acute coronary syndrome;Niccoli;Eur. Heart J.,2015

4. 2018 ESC/EACTS Guidelines on myocardial revascularization;Neumann;Eur. Heart J.,2019

5. 2017 AHA/ACC clinical performance and quality measures for adults with ST-elevation and Non-ST-elevation myocardial infarction: a report of the American College of Cardiology/American heart association task force on performance measures;Jneid;J. Am. Coll. Cardiol.,2017

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