Published on in Vol 8 , No 11 (2020) :November

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/19069, first published .
Multidimensional Machine Learning Personalized Prognostic Model in an Early Invasive Breast Cancer Population-Based Cohort in China: Algorithm Validation Study

Multidimensional Machine Learning Personalized Prognostic Model in an Early Invasive Breast Cancer Population-Based Cohort in China: Algorithm Validation Study

Multidimensional Machine Learning Personalized Prognostic Model in an Early Invasive Breast Cancer Population-Based Cohort in China: Algorithm Validation Study

Xiaorong Zhong 1 * , MD ;   Ting Luo 1 * , MD ;   Ling Deng 2 , MD, PhD ;   Pei Liu 3 , MSc ;   Kejia Hu 4 , MD ;   Donghao Lu 4 , MD, PhD ;   Dan Zheng 2 , MD ;   Chuanxu Luo 2 , MD ;   Yuxin Xie 1 , MD ;   Jiayuan Li 5 , PhD ;   Ping He 1 , MD ;   Tianjie Pu 6 , MD ;   Feng Ye 6 , PhD ;   Hong Bu 6 , MD, PhD ;   Bo Fu 3 , PhD ;   Hong Zheng 2 , MD, PhD

1 Department of Head, Neck and Mammary Gland Oncology , Cancer Center, West China Hospital , Sichuan University , Chengdu , CN

2 Laboratory of Molecular Diagnosis of Cancer , Clinical Research Center for Breast, West China Hospital , Sichuan University , Chengdu , CN

3 Big Data Research Center , School of Computer Science and Engineering , University of Electronic Science and Technology of China , Chengdu , CN

4 Department of Medical Epidemiology & Biostatistics , Karolinska Institutet , Stockholm , SE

5 Department of Epidemiology and Biostatistics , West China School of Public Health , Sichuan University , Chengdu , CN

6 Laboratory of Pathology , West China Hospital , Sichuan University , Chengdu , CN

*these authors contributed equally

Corresponding Author:

  • Hong Zheng, MD, PhD
  • Laboratory of Molecular Diagnosis of Cancer
  • Clinical Research Center for Breast, West China Hospital
  • Sichuan University
  • 37 Guoxuexiang, Wuhou District
  • Chengdu
  • CN
  • Phone: 86 2885422685
  • Email: hzheng@scu.edu.cn