Comparative evaluation of machine learning models in predicting overall survival for nasopharyngeal carcinoma using F-FDG PET-CT parameters.

Journal: Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico
PMID: 39304599

Abstract

PURPOSE: The objective of this study is to assess the prognostic efficacy of F-fluorodeoxyglucose (F-FDG) positron emission tomography/computed tomography (PET-CT) parameters in nasopharyngeal carcinoma (NPC) and identify the best machine learning (ML) prognostic model for NPC patients based on these F-FDG PET/CT parameters and clinical variables.

Authors

  • Duanyu Lin
    Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital（Fujian Branch of Fudan University Shanghai Cancer Center）, 420 Fuma Rd, Jin'an District, Fuzhou, Fujian, China.
  • Wenxi Wu
    Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital（Fujian Branch of Fudan University Shanghai Cancer Center）, 420 Fuma Rd, Jin'an District, Fuzhou, Fujian, China.
  • Zongwei Huang
    Department of General Surgery, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, China.
  • Siqi Xu
    Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital（Fujian Branch of Fudan University Shanghai Cancer Center）, 420 Fuma Rd, Jin'an District, Fuzhou, Fujian, China.
  • Ying Li
    School of Information Engineering, Chang'an University, Xi'an 710010, China.
  • Zihan Chen
    School of Data Science, University of Science and Technology of China, Hefei, PR China.
  • Yi Li
    Wuhan Zoncare Bio-Medical Electronics Co., Ltd, Wuhan, China.
  • Jinghua Lai
    Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital（Fujian Branch of Fudan University Shanghai Cancer Center）, 420 Fuma Rd, Jin'an District, Fuzhou, Fujian, China.
  • Jun Lu
    School of Acupuncture-moxibustion and Tuina, Beijing University of Chinese Medicine, Beijing 100029, China.
  • Sufang Qiu

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