Development and validation of outcome prediction model for reperfusion therapy in acute ischemic stroke using nomogram and machine learning.

Journal: Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology
PMID: 38277052

Abstract

OBJECTIVE: To develop logistic regression nomogram and machine learning (ML)-based models to predict 3-month unfavorable functional outcome for acute ischemic stroke (AIS) patients undergoing reperfusion therapy.

Authors

  • Qianwen Wang
  • Jiawen Yin
    Department of Neurology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, No. 1 DaHua Road, Dong Dan, Beijing, 100730, People's Republic of China.
  • Lei Xu
    Key Laboratory of Biomedical Information Engineering of the Ministry of Education, Department of Biomedical Engineering, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, China.
  • Jun Lu
    School of Acupuncture-moxibustion and Tuina, Beijing University of Chinese Medicine, Beijing 100029, China.
  • Juan Chen
    Department of Occupational and Environmental Health Sciences, School of Public Health, Peking University, Beijing 100191, China. chenjuan94@bjmu.edu.cn.
  • Yuhui Chen
    Department of Neurology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, No. 1 DaHua Road, Dong Dan, Beijing, 100730, People's Republic of China. cmucyh@163.com.
  • Alimu Wufuer
    Department of Neurology, the First Affiliated Hospital of Xinjiang Medical University, No. 137 South Liyushan Road, Urumqi, 830054, Xinjiang, People's Republic of China. alim013@163.com.
  • Tao Gong
    Educational Testing Service, Princeton, NJ, USA.

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