Enhanced stroke risk prediction in hypertensive patients through deep learning integration of imaging and clinical data.

Journal: BMC medical informatics and decision making
Published Date: Jul 31, 2025

Abstract

BACKGROUND: Stroke is one of the leading causes of death and disability worldwide, with a significantly elevated incidence among individuals with hypertension. Conventional risk assessment methods primarily rely on a limited set of clinical parameters and often exclude imaging-derived structural features, resulting in suboptimal predictive accuracy.

Authors

  • Hui Li
    Department of Ophthalmology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China.
  • Tianyu Zhang
    State Key Laboratory of Respiratory Disease, Joint School of Life Sciences, Guangzhou Chest Hospital, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou Medical University, Guangzhou, China.
  • Guochao Han
    Neuroelectrophysiology Department, The Second Affiliated Hospital of Qiqihar Medical College, No. 37, Zhonghua West Road, Jianhua District, Qiqihar, Heilongjiang Province, 161000, China.
  • Zonghui Huang
    Imaging Department, The Second Affiliated Hospital of Qiqihar Medical College, Qiqihar, 161000, China.
  • Huiyu Xiao
    Imaging Department, The Second Affiliated Hospital of Qiqihar Medical College, Qiqihar, 161000, China.
  • Yunzhe Ni
    Imaging Department, The Second Affiliated Hospital of Qiqihar Medical College, Qiqihar, 161000, China.
  • Bo Liu
    Wuhan United Imaging Healthcare Surgical Technology Co., Ltd., Wuhan, China.
  • Wennan Lin
    Department of General Medicine, The Second Affiliated Hospital of Qiqihar Medical College, Qiqihar, 161000, China.
  • Yuan Lin

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