Application of deep learning (3-dimensional convolutional neural network) for the prediction of pathological invasiveness in lung adenocarcinoma: A preliminary study

To compare results for radiological prediction of pathological invasiveness in lung adenocarcinoma between radiologists and a deep learning (DL) system. Ninety patients (50 men, 40 women; mean age, 66 years; range, 40–88 years) who underwent pre-operative chest computed tomography (CT) with 0.625-mm...

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Detalles Bibliográficos
Autores principales: Yanagawa, Masahiro, Niioka, Hirohiko, Hata, Akinori, Kikuchi, Noriko, Honda, Osamu, Kurakami, Hiroyuki, Morii, Eiichi, Noguchi, Masayuki, Watanabe, Yoshiyuki, Miyake, Jun, Tomiyama, Noriyuki
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Wolters Kluwer Health 2019
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6636940/
https://www.ncbi.nlm.nih.gov/pubmed/31232960
http://dx.doi.org/10.1097/MD.0000000000016119

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6636940/
https://www.ncbi.nlm.nih.gov/pubmed/31232960
http://dx.doi.org/10.1097/MD.0000000000016119

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