Prediction of axillary lymph node pathological complete response to neoadjuvant therapy using nomogram and machine learning methods

PURPOSE: To determine the feasibility of predicting the rate of an axillary lymph node pathological complete response (apCR) using nomogram and machine learning methods. METHODS: A total of 247 patients with early breast cancer (eBC), who underwent neoadjuvant therapy (NAT) were included retrospecti...

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Detalles Bibliográficos
Autores principales: Zhou, Tianyang, Yang, Mengting, Wang, Mijia, Han, Linlin, Chen, Hong, Wu, Nan, Wang, Shan, Wang, Xinyi, Zhang, Yuting, Cui, Di, Jin, Feng, Qin, Pan, Wang, Jia
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/PMC9637839/
https://www.ncbi.nlm.nih.gov/pubmed/36353547
http://dx.doi.org/10.3389/fonc.2022.1046039

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9637839/
https://www.ncbi.nlm.nih.gov/pubmed/36353547
http://dx.doi.org/10.3389/fonc.2022.1046039

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