Probe-based confocal laser endomicroscopy (pCLE) is an endoscopic technique that enables real-time histological evaluation of gastric mucosal disease during ongoing endoscopy examination. However this requires much experience, which limits the application of pCLE. The investigators designed a computer-aided diagnosis program using deep neural network to make diagnosis automatically in pCLE examination and contrast its performance with endoscopists.
Study Type
OBSERVATIONAL
Enrollment
951
When suspected lesion is observed using pCLE, endoscopist and AI will make a diagnosis independently. In addition, the endoscopist can not see the diagnosis of AI.
Endoscopic unit of Qilu Hospital Shandong University
Jinan, Shandong, China
The diagnosis efficiency of Artificial Intelligence
The primary outcome is to test the diagnostic accuracy, sensitivity, specificity, PPV, NPV of the Artificial Intelligence for diagnosing gastric mucosal disease on real-time pCLE examination.
Time frame: 24 months
Contrast the diagnosis efficiency of Artificial Intelligence with endoscopists
The secondary outcome is to compare the diagnosis efficiency (including diagnostic accuracy, sensitivity, specificity, PPV, NPV for diagnosing gastric mucosal disease on real-time pCLE examination) between Artificial Intelligence and endoscopists.
Time frame: 24 months
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