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• W4384522344 endingPage "4383" @default.
• W4384522344 startingPage "4383" @default.
• W4384522344 abstract "One of the leading causes of cancer deaths is esophageal cancer (EC) because identifying it in early stage is challenging. Computer-aided diagnosis (CAD) could detect the early stages of EC have been developed in recent years. Therefore, in this study, complete meta-analysis of selected studies that only uses hyperspectral imaging to detect EC is evaluated in terms of their diagnostic test accuracy (DTA). Eight studies are chosen based on the Quadas-2 tool results for systematic DTA analysis, and each of the methods developed in these studies is classified based on the nationality of the data, artificial intelligence, the type of image, the type of cancer detected, and the year of publishing. Deeks' funnel plot, forest plot, and accuracy charts were made. The methods studied in these articles show the automatic diagnosis of EC has a high accuracy, but external validation, which is a prerequisite for real-time clinical applications, is lacking." @default.
• W4384522344 created "2023-07-18" @default.
• W4384522344 creator A5039097516 @default.
• W4384522344 creator A5052246876 @default.
• W4384522344 creator A5069872673 @default.
• W4384522344 creator A5079305250 @default.
• W4384522344 creator A5079999978 @default.
• W4384522344 creator A5092485116 @default.
• W4384522344 date "2023-07-31" @default.
• W4384522344 modified "2023-10-18" @default.
• W4384522344 title "Systematic meta-analysis of computer-aided detection to detect early esophageal cancer using hyperspectral imaging" @default.
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