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Diagnostic evaluation of a deep learning model for optical diagnosis of colorectal cancer

Author

Listed:
  • Dejun Zhou

    (Tianjin Medical University)

  • Fei Tian

    (Tianjin Medical University)

  • Xiangdong Tian

    (Tianjin Medical University)

  • Lin Sun

    (Tianjin Medical University)

  • Xianghui Huang

    (Zhejiang University Ningbo Hospital)

  • Feng Zhao

    (Nanyang Hospital of Traditional Chinese Medicine)

  • Nan Zhou

    (Nanyang Hospital of Traditional Chinese Medicine)

  • Zuoyu Chen

    (Tianjin Medical University)

  • Qiang Zhang

    (Tianjin Medical University)

  • Meng Yang

    (Tianjin Medical University)

  • Yichen Yang

    (Tianjin Medical University)

  • Xuexi Guo

    (Tianjin First Central Hospital)

  • Zhibin Li

    (People’s First Hospital of Shangqiu)

  • Jia Liu

    (Tianjin Medical University)

  • Jiefu Wang

    (Tianjin Medical University)

  • Junfeng Wang

    (Tianjin Medical University)

  • Bangmao Wang

    (Tianjin Medical University)

  • Guoliang Zhang

    (Tianjin First Central Hospital)

  • Baocun Sun

    (Tianjin Medical University)

  • Wei Zhang

    (Wake Forest Baptist Medical Center
    Wake Forest School of Medicine)

  • Dalu Kong

    (Tianjin Medical University)

  • Kexin Chen

    (Tianjin Medical University)

  • Xiangchun Li

    (Tianjin Medical University)

Abstract

Colonoscopy is commonly used to screen for colorectal cancer (CRC). We develop a deep learning model called CRCNet for optical diagnosis of CRC by training on 464,105 images from 12,179 patients and test its performance on 2263 patients from three independent datasets. At the patient-level, CRCNet achieves an area under the precision-recall curve (AUPRC) of 0.882 (95% CI: 0.828–0.931), 0.874 (0.820–0.926) and 0.867 (0.795–0.923). CRCNet exceeds average endoscopists performance on recall rate across two test sets (91.3% versus 83.8%; two-sided t-test, p

Suggested Citation

  • Dejun Zhou & Fei Tian & Xiangdong Tian & Lin Sun & Xianghui Huang & Feng Zhao & Nan Zhou & Zuoyu Chen & Qiang Zhang & Meng Yang & Yichen Yang & Xuexi Guo & Zhibin Li & Jia Liu & Jiefu Wang & Junfeng W, 2020. "Diagnostic evaluation of a deep learning model for optical diagnosis of colorectal cancer," Nature Communications, Nature, vol. 11(1), pages 1-9, December.
    • Handle: RePEc:nat:natcom:v:11:y:2020:i:1:d:10.1038_s41467-020-16777-6
    DOI: 10.1038/s41467-020-16777-6
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