Validation the Artificial Intelligence System for Automatic Evaluation of the Extent of
Validation the Artificial Intelligence System for Automatic Evaluation of the Extent of
The operative link on gastric intestinal metaplasia assessment (OLGIM) staging systems using biopsy specimens were commonly used for histological assessment of gastric cancer risk. But its clinical application is limited for at least biopsy samples. The endoscopic grading system (EGGIM) has been shown a significant correlation with the OLGIM. The investigators designed a computer-aided diagnosis program using deep neural network to automatically evaluate the extent of IM and calculate the EGGIM scores in endoscopy examination. This study is aimed at exploring the relevance of the EGGIM scores automatically evaluated by Artificial Intelligence and OLGIM scores.
Gastric intestinal metaplasia(GIM) is an important stage in the gastric cancer(GC). The operative link on gastric intestinal metaplasia assessment (OLGIM) staging systems using biopsy specimens were commonly used for histological assessment of gastric cancer risk. However, its need to take at least 4 biopsies is not clinically feasible. The endoscopic grading system (EGGIM) has been shown a significant correlation with the OLGIM. An EGGIM score of 5 was the best cut off value for identifying OLGIM stage III/IV patients. The investigators have designed a computer-aided diagnosis program using deep neural network to automatically evaluate the extent of IM and calculate the EGGIM scores in endoscopy examination. This study is aimed at exploring the relevance of the EGGIM scores automatically evaluated by Artificial Intelligence and OLGIM scores.
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Exclusion Criteria: