Predicting lymphovascular invasion in clinically node-negative breast cancer detected by abbreviated magnetic resonance imaging: Transfer learning vs. radiomics

OBJECTIVE: To compare the performance of abbreviated breast magnetic resonance imaging (AB-MRI)-based transfer learning (TL) algorithm and radionics analysis for lymphovascular invasion (LVI) prediction in patients with clinically node-negative invasive breast cancer (IBC). METHODS: Between November...

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Detalles Bibliográficos
Autores principales: Feng, Bao, Liu, Zhuangsheng, Liu, Yu, Chen, Yehang, Zhou, Haoyang, Cui, Enming, Li, Xiaoping, Chen, Xiangmeng, Li, Ronggang, Yu, Tianyou, Zhang, Ling, Long, Wansheng
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/PMC9520481/
https://www.ncbi.nlm.nih.gov/pubmed/36185309
http://dx.doi.org/10.3389/fonc.2022.890659

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9520481/
https://www.ncbi.nlm.nih.gov/pubmed/36185309
http://dx.doi.org/10.3389/fonc.2022.890659

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