Development and validation of machine learning models based on stacked generalization to predict psychosocial maladjustment in patients with acute myocardial infarction.

Journal: BMC psychiatry
PMID:

Abstract

BACKGROUND: Psychosocial maladjustment threatens the recovery of patients with acute myocardial infarction (AMI), and early identification of patients with psychosocial maladjustment may facilitate provision of reference to targeted interventions. The aims of this study were to: (1) identify key factors influencing patient psychosocial maladjustment, and (2) develop a machine learning predictive model based on Stacked Generalization.

Authors

  • Yan-Feng Wang
    School of Nursing, Jinan University, Guangdong, 510632, China.
  • Xiao-Han Li
    MRC Laboratory of Molecular Biology, Cambridge CB2 0QH, UK.
  • Xin-Yi Zhou
    School of Nursing, Jinan University, Guangdong, 510632, China.
  • Qi-Qi Ke
    School of Nursing, Jinan University, Guangdong, 510632, China.
  • Hua-Long Ma
    School of Nursing, Jinan University, Guangdong, 510632, China.
  • Zi-Han Li
    School of Nursing, Jinan University, Guangdong, 510632, China.
  • Yi-Shang Zhuo
    School of Nursing, Jinan University, Guangdong, 510632, China.
  • Jia-Yu Liu
    School of Nursing, Jinan University, Guangdong, 510632, China.
  • Xian-Liang Liu
    School of Nursing and Health Studies, Hong Kong Metropolitan University, 1 Sheung Shing Street, Homantin, Kowloon, Hong Kong SAR, China. dxliu@hkmu.edu.hk.
  • Qiao-Hong Yang
    School of Nursing, Jinan University, Guangdong, 510632, China. yqiaohong@163.com.