In recent years,artificial intelligence has been extensively applied in the diagnosis of gastric cancer based on medical imaging.In particular,using deep learning as one of the mainstream approaches in image processing has made remarkable progress.In this paper,we also provide a comprehensive literature survey using four electronic databases,PubMed,EMBASE,Web of Science,and Cochrane.The literature search is performed until November 2020.This article provides a summary of the existing algorithm of image recognition,reviews the available datasets used in gastric cancer diagnosis and the current trends in applications of deep learning theory in image recognition of gastric cancer.covers the theory of deep learning on endoscopic image recognition.We further evaluate the advantages and disadvantages of the current algorithms and summarize the characteristics of the existing image datasets,then combined with the latest progress in deep learning theory,and propose suggestions on the applicationsof optimization algorithms.Based on the existing research and application,the label,quantity,size,resolutions,and other aspects of the image dataset are also discussed.The future developments of this field are analyzed from two perspectives including algorithm optimization and data support,aiming to improve the diagnosis accuracy and reduce the risk of misdiagnosis.
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机译:The Application of the Golden Gate Image in Film and Television Media in History Teaching: Taking the Film "Summer Concerto" as an Example =影视媒体中的金门意象在历史教学的运用--以电影《夏天协奏曲》为例