End-to-end deep learning radiomics: development and validation of a novel attention-based aggregate convolutional neural network to distinguish breast diffuse large B-cell lymphoma from breast invasive ductal carcinoma

BACKGROUND: Apart from invasive pathological examination, there is no effective method to differentiate breast diffuse large B-cell lymphoma (DLBCL) from breast invasive ductal carcinoma (IDC). In this study, we aimed to develop and validate an effective deep learning radiomics model to discriminate...

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Detalles Bibliográficos
Autores principales: Chen, Wen, Liu, Fei, Wang, Rui, Qi, Ming, Zhang, Jianping, Liu, Xiaosheng, Song, Shaoli
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AME Publishing Company 2023
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10585556/
https://www.ncbi.nlm.nih.gov/pubmed/37869296
http://dx.doi.org/10.21037/qims-22-1333

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10585556/
https://www.ncbi.nlm.nih.gov/pubmed/37869296
http://dx.doi.org/10.21037/qims-22-1333

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