The efficacy of deep learning models in the diagnosis of endometrial cancer using MRI: a comparison with radiologists

PURPOSE: To compare the diagnostic performance of deep learning models using convolutional neural networks (CNN) with that of radiologists in diagnosing endometrial cancer and to verify suitable imaging conditions. METHODS: This retrospective study included patients with endometrial cancer or non-ca...

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Detalles Bibliográficos
Autores principales: Urushibara, Aiko, Saida, Tsukasa, Mori, Kensaku, Ishiguro, Toshitaka, Inoue, Kei, Masumoto, Tomohiko, Satoh, Toyomi, Nakajima, Takahito
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9063362/
https://www.ncbi.nlm.nih.gov/pubmed/35501705
http://dx.doi.org/10.1186/s12880-022-00808-3

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9063362/
https://www.ncbi.nlm.nih.gov/pubmed/35501705
http://dx.doi.org/10.1186/s12880-022-00808-3

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