Phase-contrast magnetic resonance imaging-based predictive modelling for surgical outcomes in patients with Chiari malformation type 1 with syringomyelia: a machine learning study.

Journal: Clinical radiology
PMID: 39986143

Abstract

AIM: Prospective outcome prediction plays a crucial role in guiding preoperative decision-making in patients with Chiari malformation type I (CM-Ⅰ) with syringomyelia. Here, we aimed to develop a predictive model for postoperative outcomes in patients with CM-Ⅰ with syringomyelia by integrating clinical and radiological parameters.

Authors

  • H Wang
    Department of Mechanical Engineering, Columbia University, 500 West 120th Street, New York, NY 10027, USA.
  • L Lu
    Department of Radiotherapy, Tongling People's Hospital, Anhui, PR China.
  • B Fan
    Clinical Research and Big Data Laboratory, South China Research Center for Acupuncture and Moxibustion, Medical College of Acu-Moxi and Rehabilitation, Guangzhou University of Chinese Medicine, No. 232 Waihuandong Road, Panyu District, Guangzhou 510006, China.
  • X Xiao
    Department of Radiology, Zhengzhou Central Hospital Affiliated to Zhengzhou University, No. 195, Tongbaibei Road, Zhongyuan District, Zhengzhou 450007, China. Electronic address: xiaoxinguang126@126.com.

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