Establishment of Biliary Atresia Prognostic Classification System via Survival-Based Forward Clustering - A New Biliary Atresia Classification.

Journal: Indian journal of pediatrics
PMID:

Abstract

OBJECTIVES: To develop a machine learning algorithm with prognosis data to identify different clinical phenotypes of biliary atresia (BA) and provide instructions for choosing treatment schemes.

Authors

  • Chen Xu
    Department of Mathematics and Statistics, University of Ottawa, Ottawa, ON K1N 6N5, Canada.
  • Xing Qin
    Zhejiang Key Laboratory of Large-Scale Integrated Circuit Design, Hangzhou Dianzi University, Hangzhou 310018, China.
  • Shuyang Dai
    Department of Pediatric Surgery, Shanghai Key Laboratory of Birth Defect, Children's Hospital of Fudan University, 399 Wan Yuan Road, Shanghai, 201102, China.
  • Zhen Shen
    Institute of Machine Learning and Systems Biology, School of Electronics and Information Engineering, Tongji University, Shanghai, 201804, P. R. China.
  • Yifan Yang
    College of Food Science, Sichuan Agricultural University, Ya'an 625014, China.
  • Yanlei Huang
    Department of Pediatric Surgery, Shanghai Key Laboratory of Birth Defect, Children's Hospital of Fudan University, 399 Wan Yuan Road, Shanghai, 201102, China.
  • Song Sun
    School of Big Data & Software Engineering, Chongqing University, Chongqing 401331, China.
  • Shan Zheng
    Department of Pediatric Surgery, Shanghai Key Laboratory of Birth Defect, Children's Hospital of Fudan University, 399 Wan Yuan Road, Shanghai, 201102, China. szheng@shmu.edu.cn.
  • Mengyun Wu
    School of Statistics and Management, Shanghai University of Finance and Economics, 777 Guoding Road, Shanghai, 200433, China. wu.mengyun@mail.shufe.edu.cn.
  • Gong Chen
    Departement of Medical Oncology, Lung Cancer and Gastrointestinal Unit, Hunan Cancer Hospital/Affiliated Cancer Hospital of Xiangya School of Medicine, Changsha 410013, China.