Performance comparison between two computer-aided detection colonoscopy models by trainees using different false positive thresholds: a cross-sectional study in Thailand

Performance comparison between two computer-aided detection colonoscopy models by trainees using different false positive thresholds: a cross-sectional study in Thailand

Background/Aims This study aims to compare polyp detection performance of “Deep-GI,” a newly developed artificial intelligence (AI) model, to a previously validated AI model computer-aided polyp detection (CADe) using various false positive (FP) thresholds and determining the best threshold for each...

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Bibliographic Details
Main Authors: Kasenee Tiankanon, Julalak Karuehardsuwan, Satimai Aniwan, Parit Mekaroonkamol, Panukorn Sunthornwechapong, Huttakan Navadurong, Kittithat​ Tantitanawat, Krittaya Mekritthikrai, Salin Samutrangsi, Peerapon Vateekul, Rungsun Rerknimitr
Format: Article
Language:English
Published: Korean Society of Gastrointestinal Endoscopy 2024-03-01
Series:Clinical Endoscopy
Subjects:
artificial intelligence
colonoscopy
computational intelligence
endoscopy
polyps
Online Access:http://www.e-ce.org/upload/pdf/ce-2023-145.pdf

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