Machine learning algorithms predict breast cancer incidence risk: a data-driven retrospective study based on biochemical biomarkers.

Journal: BMC cancer
Published Date:

Abstract

BACKGROUND: Current breast cancer prediction models typically rely on personal information and medical history, with limited inclusion of blood-based biomarkers. This study aimed to identify novel breast cancer risk factors using machine learning algorithms. By integrating both personal clinical factors and peripheral blood biochemical biomarkers, it sought to enhance the understanding of breast cancer risk.

Authors

  • Qianqian Guo
    National Cancer Center/Cancer Hospital of Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China.
  • Peng Wu
    Department of Orthopedics, General Hospital of Ningxia Medical University, Yinchuan, China.
  • Junhao He
    School of Computer Science, Northwestern Polytechnical University, West Youyi Road 127, Xi'an, 710072, China.
  • Ge Zhang
    Lab of Brain and Gut Research, School of Chinese Medicine, Hong Kong Baptist University, 7 Baptist University Road, Hong Kong, People's Republic of China.
  • Wu Zhou
    School of Medical Information Engineering, Guangzhou University of Chinese Medicine, Guangzhou, China, 510006.
  • Qianjun Chen
    State Key Laboratory of Traditional Chinese Medicine Syndrome/Breast Department, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangdong Provincial Hospital of Chinese Medicine, Guangdong Provincial Academy of Chinese Medical Sciences, Guangzhou, Guangdong, China. cqj55@163.com.

Keywords

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