Deep neural network for the prediction of KRAS, NRAS, and BRAF genotypes in left-sided colorectal cancer based on histopathologic images.

Journal: Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
PMID: 38759471

Abstract

BACKGROUND: The KRAS, NRAS, and BRAF genotypes are critical for selecting targeted therapies for patients with metastatic colorectal cancer (mCRC). Here, we aimed to develop a deep learning model that utilizes pathologic whole-slide images (WSIs) to accurately predict the status of KRAS, NRAS, and BRAF.

Authors

  • Xuejie Li
    3 School of Mechanical Engineering, Tianjin University , Tianjin, China .
  • Xianda Chi
    Department of Gastrointestinal Surgery, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, PR China.
  • Pinjie Huang
    Department of Anaesthesia, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, PR China.
  • Qiong Liang
    Department of Pathology, The Third Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.
  • Jianpei Liu
    Department of Gastrointestinal Surgery, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, PR China. Electronic address: liujpei2@sysu.edu.cn.

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