학술논문
AIは何をみて大腸pT1b癌を診断しているか？：Class Activation Mappingからみた検討 / WHICH REGION DOES ARTIFICIAL INTELLIGENCE LOOK AT TO PREDICT T1B COLORECTAL CANCER? ANALYSIS BASED ON CLASS ACTIVATION MAPPING
Document Type
Journal Article
Author
Source
日本消化器内視鏡学会雑誌 / GASTROENTEROLOGICAL ENDOSCOPY. 2021, 63(6):1232
Subject
Language
Japanese
ISSN
0387-1207
1884-5738
1884-5738
Abstract
Results: CAM images were successfully generated for all 226 images. The level of concordance between the ROI defined by AI and the ROI that was defined by expert endoscopists was excellent in 39％, fair in 34％ and poor in 27％. In images showing poor concordance, the ROI defined by AI was distant from the T1b cancer. After excluding lesions with poor concordance, the vast majority (91％) of the ROI defined by AI was concordant with the ROI containing endoscopists’ identification of red color, and a small proportion (21％) of the ROI defined by AI revealed bleeding. Among the lesions detected by AI, the surface morphology was depressed in 39％, flat in 5％ and protruding in 57％. Fold convergence was observed in 34％ of the ROI defined by AI.