Predicting radiation pneumonitis in lung cancer using machine learning and multimodal features: a systematic review and meta-analysis of diagnostic accuracy.

Abstract

Authors

• Zhi Chen
  Duke University.
• GuangMing Yi
  Department of Cancer Center, The Second Affiliated Hospital of Chongqing Medical University, No. 288 Tianwen Road, Nan'an District, Chongqing, 400010, China.
• Xinyan Li
  Institute for Brain Research, Wuhan Center of Brain Science, Huazhong University of Science and Technology, Wuhan, 430030, China. lixinyan1026@163.com.
• Bo Yi
  1 Department of General Surgery, Third Xiangya Hospital, Central South University , Changsha, China .
• XiaoHui Bao
  Department of Cancer Center, The Second Affiliated Hospital of Chongqing Medical University, No. 288 Tianwen Road, Nan'an District, Chongqing, 400010, China.
• Yin Zhang
  Department of Radiation Oncology, Rutgers-Cancer Institute of New Jersey, Rutgers-Robert Wood Johnson Medical School, New Brunswick, NJ, United States.
• Xiaoyue Zhang
  Ping An Healthcare Technology, Beijing, China.
• ZhenZhou Yang
  Department of Cancer Center, The Second Affiliated Hospital of Chongqing Medical University, No. 288 Tianwen Road, Nan'an District, Chongqing, 400010, China. yangzz@cqmu.edu.cn.
• Zhengjun Guo
  Department of Cancer Center, The Second Affiliated Hospital of Chongqing Medical University, No. 288 Tianwen Road, Nan'an District, Chongqing, 400010, China. guozhengjun@hospital.cqmu.edu.cn.

Keywords

External Resources