Area of research
Surgery · Oncology
Research interest
Research topics from publications: Diagnosing chronic atrophic gastritis by gastroscopy using artificial intelligence. Representative work: BACKGROUND: The sensitivity of endoscopy in diagnosing chronic atrophic gastritis is only 42%, and multipoint biopsy, despite being more accurate, is not always available. AIMS: This study aimed to construct a convolutional neural network to improve the diagnostic rate of chronic atrophic gastritis. METHODS: We collected 5470 images of the gastric antrums of 1699 patients and labeled them with their pathological findings. Of these, 3042 images depicted atrophic gastritis and 2428 did not. We designed and trained a convolutional neural network-chronic atrophic gastritis model to diagnose atrophic gastritis accurately, verified by five-fold cross-validation. Moreover, the diagnoses of the deep
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