Deep Learning Computer-aided Polyp Detection Reduces Adenoma Miss Rate: A United States Multi-center Randomized Tandem Colonoscopy Study (CADeT-CS Trial)

Artificial intelligence-based computer-aided polyp detection (CADe) systems are intended to address the issue of missed polyps during colonoscopy. The effect of CADe during screening and surveillance colonoscopy has not previously been studied in a United States (U.S.) population. We conducted a pro...

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Vydané v:	Clinical gastroenterology and hepatology Ročník 20; číslo 7; s. 1499
Hlavní autori:	Glissen Brown, Jeremy R, Mansour, Nabil M, Wang, Pu, Chuchuca, Maria Aguilera, Minchenberg, Scott B, Chandnani, Madhuri, Liu, Lin, Gross, Seth A, Sengupta, Neil, Berzin, Tyler M
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	United States 01.07.2022
Predmet:	Adenoma Detection Rate Computer-aided Detection Randomized Tandem Colonoscopy Study Adenoma Miss Rate Deep Learning
ISSN:	1542-7714, 1542-7714
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