A multi-view prognostic model for diffuse large B-cell lymphoma based on kernel canonical correlation analysis and support vector machine.

Journal: BMC cancer
PMID: 39639258

Abstract

BACKGROUND AND OBJECTIVE: Positron emission tomography/computed tomography (PET/CT) is recommended as the standard imaging modality for diffuse large B-cell lymphoma (DLBCL) staging. However, many studies have neglected the role of patients' prognostic factors with respect to imaging PET/CT of quantitative features. In this paper, a multi-view learning (MVL) model is established to make full use of both clinical and imaging data to predict the prognosis of DLBCL patients and thereby assist doctors in decision-making.

Authors

  • Yanhong Luo
    Hunan Children's Hospital, Changsha 410000, China.
  • Yongao Li
    Department of Health Statistics, School of Public Health, Shanxi Medical University, Taiyuan, 030001, China.
  • Zhenhuan Yang
    Department of Health Statistics, School of Public Health, Shanxi Medical University, Taiyuan, 030001, China.
  • Yanbo Zhang
    Department of Psychiatry, University of Alberta, Edmonton, Canada.
  • Hongmei Yu
    Department of Neurology, The Second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China.
  • Zhiqiang Zhao
    Institute of Geotechnical Engineer, College of Architecture and Civil Engineering, Beijing University of Technology, Beijing 100124, China.
  • Kai Yu
  • Yujiao Guo
    Department of Health Statistics, School of Public Health, Shanxi Medical University, Taiyuan, 030001, China.
  • Xueman Wang
    Department of Health Statistics, School of Public Health, Shanxi Medical University, Taiyuan, 030001, China.
  • Na Yang
    Department of Ultrasound, Affiliated Hospital of Jilin Medical College, Jilin, China.
  • Yan Zhang
    Affiliated Hospital of Liaoning University of Traditional Chinese Medicine, Shenyang, 110032, China.
  • Tingting Zheng
    College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, 110001, China. Electronic address: zt18638218568@163.com.
  • Jie Zhou
    Departments of Ultrasound, Jiading District Central Hospital Affiliated Shanghai University of Medicine &Health Sciences, Shanghai, China.

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