Machine learning-based model for predicting outcomes in cerebral hemorrhage patients with leukemia.

Journal: European journal of radiology
Published Date: Jun 1, 2024

Abstract

BACKGROUND AND PURPOSE: Intracranial hemorrhage (ICH) in leukemia patients progresses rapidly with high mortality. Limited data are available on imaging studies in this population. The study aims to develop prediction models for 7-day and short-term mortality risk based on the non-contrast computed tomography (NCCT) image features.

Authors

  • Lu Shi
    Department of Pharmacy, Jianghan University, Wuhan, 430056, China.
  • Ping Yin
    Department of Radiology, Peking University People's Hospital, 11 Xizhimen Nandajie, Xicheng District, Beijing, 100044, People's Republic of China.
  • Cancan Chen
    China Mobile Research Institute, Beijing, 100053, China. Electronic address: chencancan@chinamobile.com.
  • Qianrui Fan
    Institute of Research, Ocean International Center, InferVision, Chaoyang District, Beijing, 100025, China.
  • Chao Sun
    Hospital for Skin Diseases and Institute of Dermatology, Chinese Academy of Medical Sciences and Peking Union Medical College, Nanjing, China.
  • Dawei Wang
    Institute of Advanced Research, Infervision Medical Technology Co., Ltd, Beijing, China.
  • Jin Cheng
    School of Medical Technology, Qiqihar Medical University, Qiqihar, 161006, Heilongjiang, China.
  • Nan Hong
    Department of Radiology, Peking University People's Hospital, Beijing, China.

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