Machine Learning for Mortality Prediction in Patients With Heart Failure With Mildly Reduced Ejection Fraction
Pengchao Tian(Chinese Academy of Medical Sciences & Peking Union Medical College), Yuhui Zhang(Chinese Academy of Medical Sciences & Peking Union Medical College), Boping Huang(Chinese Academy of Medical Sciences & Peking Union Medical College), Jiayu Feng(Chinese Academy of Medical Sciences & Peking Union Medical College), Jian Zhang(Chinese Academy of Medical Sciences & Peking Union Medical College), Xuemei Zhao(Chinese Academy of Medical Sciences & Peking Union Medical College), Qiong Zhou(Henan University of Technology), Mei Zhai(Chinese Academy of Medical Sciences & Peking Union Medical College), Liyan Huang(Sun Yat-sen University), Yan Huang(Sun Yat-sen University), Lin Liang(Chinese Academy of Medical Sciences & Peking Union Medical College)
Cited by 17
Related Papers
Empagliflozin in Heart Failure with a Preserved Ejection Fraction
|New England Journal of Medicine|2021|4.6k
Patient Phenotype Profiling in Heart Failure with Preserved Ejection Fraction to Guide Therapeutic Decision Making. A Scientific Statement of the Heart Failure Association, the European Heart Rhythm Association of the European Society of Cardiology, and the European Society of Hypertension
|European Journal of Heart Failure|2023|187
Precipitating Factors and 90-Day Outcome of Acute Heart Failure: A Report from the Intercontinental GREAT Registry
|European Journal of Heart Failure|2016|149
Baseline Characteristics of Patients with Heart Failure with Preserved Ejection Fraction in the EMPEROR-Preserved Trial
|European Journal of Heart Failure|2020|135