Machine-learning-based models assist the prediction of pulmonary embolism in autoimmune diseases: A retrospective, multicenter study.

Journal: Chinese medical journal
Published Date: Jun 12, 2024

Abstract

BACKGROUND: Pulmonary embolism (PE) is a severe and acute cardiovascular syndrome with high mortality among patients with autoimmune inflammatory rheumatic diseases (AIIRDs). Accurate prediction and timely intervention play a pivotal role in enhancing survival rates. However, there is a notable scarcity of practical early prediction and risk assessment systems of PE in patients with AIIRD.

Authors

  • Ziwei Hu
    Institute of Pharmaceutical Analysis , College of Pharmacy , Jinan University , Guangzhou , Guangdong 510632 , China . Email: haibo.zhou@jnu.edu.cn ; Email: jzjjackson@hotmail.com ; Email: tghao@jnu.edu.cn.
  • Yangyang Hu
    Reproductive Medicine Center, Obstetrics and Gynecology, The Second Affiliated Hospital of Wenzhou Medical University, Wenzhou, China.
  • Shuoqi Zhang
    Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China.
  • Li Dong
    Department of Cardiovascular Surgery, West China Hospital, Sichuan University, Chengdu, China. donglikn199@163.com.
  • Xiaoqi Chen
    Key Laboratory for Control Theory & Applications in Complicated Systems, Tianjin University of Technology, Tianjin 300384, China.
  • Huiqin Yang
    Department of Rheumatology, Wuhan No.1 Hospital, Wuhan, Hubei 430022, China.
  • Linchong Su
    Department of Rheumatology, Minda Hospital of Hubei Minzu University, Enshi, Hubei 445000, China.
  • Xiaoqiang Hou
    Department of Rheumatology and Immunology, The First College of Clinical Medical Science, China Three Gorges University, Yichang, Hubei 443003, China.
  • Xia Huang
    College of Electrical Engineering and Automation, Shandong University of Science and Technology, Qingdao 266590, China.
  • Xiaolan Shen
    Department of Rheumatology and Immunology, The First College of Clinical Medical Science, China Three Gorges University, Yichang, Hubei 443003, China.
  • Cong Ye
    School of Microelectronics, Key Laboratory of Intelligent Sensing System and Security, Ministry of Education, Hubei University, Wuhan 430062, China.
  • Wei Tu
    Department of Rheumatology and Immunology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China.
  • Yu Chen
    State Key Laboratory of Oral Diseases & National Center for Stomatology & National Clinical Center for Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu, Sichuan, China.
  • Yuxue Chen
    Department of Rheumatology and Immunology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China.
  • Shaozhe Cai
    Department of Rheumatology and Immunology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China.
  • Jixin Zhong
    Department of Rheumatology and Immunology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China.
  • Lingli Dong
    Department of Rheumatology and Immunology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China.

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