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Copyright ©The Author(s) 2021.
Artif Intell Gastrointest Endosc. Aug 28, 2021; 2(4): 179-184
Published online Aug 28, 2021. doi: 10.37126/aige.v2.i4.179
Table 1 Artificial intelligence methods for gastrointestinal angiodysplasia detection[17]
Artificial intelligence
Description
Function
Advantages
Disadvantages
Machine learning Ability of a computer program to learn Discern logic-based rules from input and output dataAutomation of tasksRequires high-quality data likely to have some causal link
Algorithm workflow improves performanceDetect patterns between input and output data
Artificial neural network Use of weighted/graded signals to perceive dataAdaptive learningMapping performance between input and output dataRequires labeled data
Use of computational communicationAdaptive learning capabilityRequires large volumes of data
Convolutional neural network Image detection Computer visionHighly accurate image recognition and classificationHighly dependent on a training modelor models
Interpretation through three-dimensional convolutional layersLimited by image rotation or orientation