Development of a deep learning model for classifying thymoma as Masaoka-Koga stage I or II via preoperative CT images

BACKGROUND: Accurate thymoma staging via computed tomography (CT) images is difficult even for experienced thoracic doctors. Here we developed a preoperative staging tool differentiating Masaoka-Koga (MK) stage I patients from stage II patients using CT images. METHODS: CT images of 174 thymoma pati...

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Detalles Bibliográficos
Autores principales: Yang, Lei, Cai, Wenjia, Yang, Xiaoyu, Zhu, Haoshuai, Liu, Zhenguo, Wu, Xi, Lei, Yiyan, Zou, Jianyong, Zeng, Bo, Tian, Xi, Zhang, Rongguo, Luo, Honghe, Zhu, Ying
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AME Publishing Company 2020
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7186715/
https://www.ncbi.nlm.nih.gov/pubmed/32355731
http://dx.doi.org/10.21037/atm.2020.02.183

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7186715/
https://www.ncbi.nlm.nih.gov/pubmed/32355731
http://dx.doi.org/10.21037/atm.2020.02.183

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