Cargando…
Artificial intelligence-based assessments of colonoscopic withdrawal technique: a new method for measuring and enhancing the quality of fold examination
Background This study aimed to develop an artificial intelligence (AI)-based system for measuring fold examination quality (FEQ) of colonoscopic withdrawal technique. We also examined the relationship between the system’s evaluation of FEQ and FEQ scores from experts, and adenoma detection rate (AD...
Autores principales: | Liu, Wei, Wu, Yu, Yuan, Xianglei, Zhang, Jingyu, Zhou, Yao, Zhang, Wanhong, Zhu, Peipei, Tao, Zhang, He, Long, Hu, Bing, Yi, Zhang |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Georg Thieme Verlag KG
2022
|
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9500011/ https://www.ncbi.nlm.nih.gov/pubmed/35391493 http://dx.doi.org/10.1055/a-1799-8297 |
Ejemplares similares
-
Colonoscopic withdrawal time and adenoma detection in the right colon
por: Yun, Gee Young, et al.
Publicado: (2018) -
AlphaFold, Artificial
Intelligence (AI), and Allostery
por: Nussinov, Ruth, et al.
Publicado: (2022) -
Faster colonoscope withdrawal time without impaired detection using EndoRings
por: Thygesen, John C., et al.
Publicado: (2018) -
Physician sentiment toward artificial intelligence (AI) in colonoscopic practice: a survey of US gastroenterologists
por: Wadhwa, Vaibhav, et al.
Publicado: (2020) -
Artificial Intelligence for Detecting and Delineating Margins of Early ESCC Under WLI Endoscopy
por: Liu, Wei, et al.
Publicado: (2022)