Diagnosis of architectural distortion on digital breast tomosynthesis using radiomics and deep learning

PURPOSE: To implement two Artificial Intelligence (AI) methods, radiomics and deep learning, to build diagnostic models for patients presenting with architectural distortion on Digital Breast Tomosynthesis (DBT) images. MATERIALS AND METHODS: A total of 298 patients were identified from a retrospect...

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Detalles Bibliográficos
Autores principales: Chen, Xiao, Zhang, Yang, Zhou, Jiahuan, Wang, Xiao, Liu, Xinmiao, Nie, Ke, Lin, Xiaomin, He, Wenwen, Su, Min-Ying, Cao, Guoquan, Wang, Meihao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Oncology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9792864/
https://www.ncbi.nlm.nih.gov/pubmed/36582788
http://dx.doi.org/10.3389/fonc.2022.991892

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9792864/
https://www.ncbi.nlm.nih.gov/pubmed/36582788
http://dx.doi.org/10.3389/fonc.2022.991892

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