Predicting breast cancer metastasis by using serum biomarkers and clinicopathological data with machine learning technologies.

Journal: International journal of medical informatics
Published Date: May 7, 2019

Abstract

BACKGROUND: Approximately 10%-15% of patients with breast cancer die of cancer metastasis or recurrence, and early diagnosis of it can improve prognosis. Breast cancer outcomes may be prognosticated on the basis of surface markers of tumor cells and serum tests. However, evaluation of a combination of clinicopathological features may offer a more comprehensive overview for breast cancer prognosis.

Authors

  • Yi-Ju Tseng
    Department of Laboratory Medicine, Chang Gung Memorial Hospital at Linkou, Taoyuan City, Taiwan.
  • Chuan-En Huang
    Department of Information Management, Chang Gung University, Taiwan.
  • Chiao-Ni Wen
    Department of Laboratory Medicine, Chang Gung Memorial Hospital at Linkou, Taiwan; Department of Medical Biotechnology and Laboratory Science, Chang Gung University, Taiwan.
  • Po-Yin Lai
    Department of Laboratory Medicine, Chang Gung Memorial Hospital at Linkou, Taiwan.
  • Min-Hsien Wu
    Graduate Institute of Biomedical Engineering, Chang Gung University, Taoyuan City, Taiwan; Division of Haematology/Oncology, Department of Internal Medicine, Chang Gung Memorial Hospital at Linkou, Taoyuan City, Taiwan; Biosensor Group, Biomedical Engineering Research Center, Chang Gung University, Taoyuan City, Taiwan.
  • Yu-Chen Sun
    Department of Laboratory Medicine, Chang Gung Memorial Hospital at Linkou, Taiwan.
  • Hsin-Yao Wang
    Department of Laboratory Medicine, Chang Gung Memorial Hospital at Linkou, Taoyuan City, Taiwan.
  • Jang-Jih Lu
    Department of Laboratory Medicine, Chang Gung Memorial Hospital at Linkou, Taoyuan City, Taiwan.

Keywords

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