Computed tomography-based deep-learning prediction of induction chemotherapy treatment response in locally advanced nasopharyngeal carcinoma.

Journal: Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al]
PMID: 34817635

Abstract

BACKGROUND: Deep learning methods have great potential to predict treatment response. The objective of this study was to evaluate and validate the predictive performance of the computed tomography (CT)-based model using deep learning features for identification of responders and nonresponders to induction chemotherapy (IC) in nasopharyngeal carcinoma (NPC).

Authors

  • Yuhan Yang
    West China School of Medicine, Sichuan University, No.17 People's South Road, Chengdu, 610041, Sichuan, China. Electronic address: yyh_1023@163.com.
  • Manni Wang
    Cancer Center, West China Hospital, Sichuan University and Collaborative Innovation Center Emergency Department Department of Nuclear Medicine, West China Hospital, Sichuan University, Chengdu, People's Republic of China.
  • Ke Qiu
    West China School of Medicine, Sichuan University, No. 17 People's South Road, 610041, Chengdu, Sichuan, China.
  • Yixi Wang
    West China School of Medicine, Sichuan University, No.17 People's South Road, Chengdu, 610041, Sichuan, China. Electronic address: 653508203@qq.com.
  • Xuelei Ma

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