A prospective and comparative study on improving the diagnostic accuracy of early gastric cancer based on deep convolutional neural network real-time diagnosis system (with video).

Journal: Surgical endoscopy
PMID: 39843600

Abstract

BACKGROUND: Endoscopic diagnosis of early gastric cancer (EGC) is a challenge. It is not clear whether deep convolutional neural network (DCNN) model could improve the endoscopists' diagnostic performance.

Authors

  • Jie Feng
  • Yaoping Zhang
    Department of Gastroenterology, Lanzhou University Second Hospital, Lanzhou, Gansu Province, China.
  • Zhijun Feng
    Southern Medical University, Guangzhou, Guangdong Province, China.
  • Huiming Ma
    Department of Gastroenterology, Lanzhou University Second Hospital, Lanzhou, Gansu Province, China.
  • Yani Gou
    Department of Gastroenterology, Lanzhou University Second Hospital, Lanzhou, Gansu Province, China.
  • Pengfei Wang
    Department of Anesthesiology, The Second Xiangya Hospital, Central South University, Changsha, China.
  • Yanhu Feng
    Department of Gastroenterology, Lanzhou University Second Hospital, Lanzhou, Gansu Province, China.
  • Xiang Wang
    Department of Thoracic Surgery, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China.
  • Xiaojun Huang
    Department of Gastroenterology, Lanzhou University Second Hospital, Lanzhou, Gansu Province, China.

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