Novel algorithm for diagnosis of Arrhythmogenic cardiomyopathy and dilated cardiomyopathy: Key gene expression profiling using machine learning-Reference-Cited by-全球学者库

Novel algorithm for diagnosis of Arrhythmogenic cardiomyopathy and dilated cardiomyopathy: Key gene expression profiling using machine learning

Published:2022-12-19 Issue:3 Volume:25 Page:
ISSN:1099-498X
Container-title:The Journal of Gene Medicine
language:en
Short-container-title:The Journal of Gene Medicine

Author:

Zhang Youming¹,Xie Jiaxi²,Wu Yizhang¹,Zhang Baowei¹,Zhou Chunjiang³,Gao Xiaotong¹,Xie Xin¹,Li Xiaorong¹,Yu Jinbo¹,Wang Xuecheng¹,Cheng Dian¹,Zhou Jian¹,Chen Zijun¹,Fan Fenghua¹,Zhou Xiujuan²,Yang Bing¹

Affiliation:

1. Center of Cardiology, Shanghai East Hospital Tongji University School of Medicine Shanghai China

2. Department of Cardiology The First Affiliated Hospital of Nanjing Medical University Nanjing China

3. Center of Cardiology, Shanghai East Hospital Nanjing Medical University Shanghai China

Publisher

Wiley

Subject

Genetics (clinical),Drug Discovery,Genetics,Molecular Biology,Molecular Medicine

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/jgm.3468

Reference33 articles.

1. 2019 HRS expert consensus statement on evaluation, risk stratification, and management of arrhythmogenic cardiomyopathy

2. Classification of the cardiomyopathies: a position statement from the european society of cardiology working group on myocardial and pericardial diseases

3. Restrictive Cardiomyopathy

4. Genetic Risk of Arrhythmic Phenotypes in Patients With Dilated Cardiomyopathy

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