Development and Multi-center validation of a machine learning Model for advanced colorectal neoplasms screening.

Journal: Computers in biology and medicine
PMID: 40157315

Abstract

BACKGROUND: In colorectal cancer (CRC) screening programs, accurately identifying individuals at high risk for advanced colorectal neoplasia (ACN) is essential as they require further colonoscopy, early intervention, and monitoring follow-up. This study aimed to develop a machine learning (ML)-based risk prediction model, serving as an effective tool for the early identification of high-risk individuals for ACN.

Authors

  • Mingqing Zhang
    Department of Colorectal Surgery, Tianjin Union Medical Center, Tianjin, China.
  • Yongdan Zhang
    Department of Colorectal Surgery, Tianjin Union Medical Center, Tianjin, China.
  • Lizhong Zhao
    Department of Colorectal Surgery, Tianjin Union Medical Center, The First Affiliated Hospital of Nankai University, Tianjin, China; Tianjin Institute of Coloproctology, Tianjin, China.
  • Haoren Jing
    Department of Colorectal Surgery, Tianjin Union Medical Center, Tianjin, China.
  • Xinyu Gao
    Department of Colorectal Surgery, Tianjin Union Medical Center, The First Affiliated Hospital of Nankai University, Tianjin, China; Tianjin Institute of Coloproctology, Tianjin, China.
  • Tianhao Li
    Tianjin Union Medical Center, Tianjin Medical University, Tianjin, China.
  • Zhicheng Pu
    Nankai University School of Medicine, Nankai University, Tianjin, China.
  • Shiwu Zhang
  • Xipeng Zhang
    Department of Colorectal Surgery, Tianjin Union Medical Center, Tianjin, China.

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