Effects of deep learning on radiologists’ and radiology residents’ performance in identifying esophageal cancer on CT

OBJECTIVE: To investigate the effectiveness of a deep learning model in helping radiologists or radiology residents detect esophageal cancer on contrast-enhanced CT images. METHODS: This retrospective study included 250 and 25 patients with and without esophageal cancer, respectively, who underwent...

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Detalles Bibliográficos
Autores principales: Yasaka, Koichiro, Hatano, Sosuke, Mizuki, Masumi, Okimoto, Naomasa, Kubo, Takatoshi, Shibata, Eisuke, Watadani, Takeyuki, Abe, Osamu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The British Institute of Radiology. 2023
Materias:
AI in imaging and therapy: innovations ethics and impact: Full Paper
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10546446/
https://www.ncbi.nlm.nih.gov/pubmed/37000686
http://dx.doi.org/10.1259/bjr.20220685

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10546446/
https://www.ncbi.nlm.nih.gov/pubmed/37000686
http://dx.doi.org/10.1259/bjr.20220685

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