Magnetic resonance imaging-based deep learning imaging biomarker for predicting functional outcomes after acute ischemic stroke.

Journal: European journal of radiology
PMID: 38447430

Abstract

PURPOSE: Clinical risk scores are essential for predicting outcomes in stroke patients. The advancements in deep learning (DL) techniques provide opportunities to develop prediction applications using magnetic resonance (MR) images. We aimed to develop an MR-based DL imaging biomarker for predicting outcomes in acute ischemic stroke (AIS) and evaluate its additional benefit to current risk scores.

Authors

  • Tzu-Hsien Yang
    Department of Biomedical Engineering, National Cheng Kung University, No. 1, University Road, Tainan 701, Taiwan. Electronic address: thyangza@gs.ncku.edu.tw.
  • Ying-Ying Su
    Department of Radiology, Ditmanson Medical Foundation Chia-Yi Christian Hospital, Chiayi City, Taiwan.
  • Chia-Ling Tsai
    Computer Science Department, Queens College, CUNY, Queens, New York, USA.
  • Kai-Hsuan Lin
    Department of Computer Science and Information Engineering, National Chung Cheng University, Chiayi, Taiwan.
  • Wei-Yang Lin
    Department of Computer Science and Information Engineering, National Chung Cheng University, Chiayi Taiwan.
  • Sheng-Feng Sung
    Division of Neurology, Department of Internal Medicine, Ditmanson Medical Foundation Chiayi Christian Hospital, Chiayi City, Taiwan; Department of Information Management and Institute of Healthcare Information Management, National Chung Cheng University, Chiayi County, Taiwan; Department of Nursing, Min-Hwei Junior College of Health Care Management, Tainan, Taiwan.

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