Development and evaluation of a deep learning model to improve the usability of polyp detection systems during interventions

BACKGROUND: The efficiency of artificial intelligence as computer‐aided detection (CADe) systems for colorectal polyps has been demonstrated in several randomized trials. However, CADe systems generate many distracting detections, especially during interventions such as polypectomies. Those distract...

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Detalles Bibliográficos
Autores principales: Brand, Markus, Troya, Joel, Krenzer, Adrian, Saßmannshausen, Zita, Zoller, Wolfram G., Meining, Alexander, Lux, Thomas J., Hann, Alexander
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2022
Materias:
Endoscopy
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9189459/
https://www.ncbi.nlm.nih.gov/pubmed/35511456
http://dx.doi.org/10.1002/ueg2.12235

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9189459/
https://www.ncbi.nlm.nih.gov/pubmed/35511456
http://dx.doi.org/10.1002/ueg2.12235

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