Integrating Clinical Data and Radiomics and Deep Learning Features for End-to-End Delayed Cerebral Ischemia Prediction on Noncontrast CT.

Journal: AJNR. American journal of neuroradiology
PMID: 39025637

Abstract

BACKGROUND AND PURPOSE: Delayed cerebral ischemia is hard to diagnose early due to gradual, symptomless development. This study aimed to develop an automated model for predicting delayed cerebral ischemia following aneurysmal SAH on NCCT.

Authors

  • Qi-Qi Ban
    From the Department of Radiology (Q.-q.B., W.W., Y.Z., H.Q.), Affiliated Hospital of Yangzhou University, Yangzhou, China.
  • Hao-Tian Zhang
    School of Mathematics and Computer Science, Northwest Minzu University, Lanzhou, 730030, People's Republic of China.
  • Wei Wang
    State Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences, University of Macau, Macau 999078, China.
  • Yi-Fan Du
    College of Medical Imaging (Q.-q.B., Y.-f.D.), Dalian Medical University, Dalian, China.
  • Yi Zhao
    Department of Biostatistics and Health Data Science, Indiana University School of Medicine.
  • Ai-Jun Peng
    Department of Neurosurgery (A.-j.P.), Affiliated Hospital of Yangzhou University, Yangzhou, China.
  • Hang Qu

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