Utility of an artificial intelligence system for classification of esophageal lesions when simulating its clinical use

Previous reports have shown favorable performance of artificial intelligence (AI) systems for diagnosing esophageal squamous cell carcinoma (ESCC) compared with endoscopists. However, these findings don’t reflect performance in clinical situations, as endoscopists classify lesions based on both magn...

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Detalles Bibliográficos
Autores principales: Tajiri, Ayaka, Ishihara, Ryu, Kato, Yusuke, Inoue, Takahiro, Matsueda, Katsunori, Miyake, Muneaki, Waki, Kotaro, Shimamoto, Yusaku, Fukuda, Hiromu, Matsuura, Noriko, Egawa, Satoshi, Yamaguchi, Shinjiro, Ogiyama, Hideharu, Ogiso, Kiyoshi, Nishida, Tsutomu, Aoi, Kenji, Tada, Tomohiro
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9035159/
https://www.ncbi.nlm.nih.gov/pubmed/35461350
http://dx.doi.org/10.1038/s41598-022-10739-2

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9035159/
https://www.ncbi.nlm.nih.gov/pubmed/35461350
http://dx.doi.org/10.1038/s41598-022-10739-2

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