Predicting Response of Triple-Negative Breast Cancer to Neoadjuvant Chemotherapy Using a Deep Convolutional Neural Network–Based Artificial Intelligence Tool

PURPOSE: Achieving a pathological complete response (pCR) to neoadjuvant chemotherapy (NAC) is associated with improved patient outcomes in triple-negative breast cancer (TNBC). Currently, there are no validated predictive biomarkers for the response to NAC in TNBC. We developed and validated a deep...

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Detalles Bibliográficos
Autores principales: Krishnamurthy, Savitri, Jain, Parag, Tripathy, Debu, Basset, Roland, Randhawa, Ramandeep, Muhammad, Hassan, Huang, Wei, Yang, Hua, Kummar, Shivaani, Wilding, George, Roy, Rajat
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Wolters Kluwer Health 2023
Materias:
ORIGINAL REPORTS
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10530970/
https://www.ncbi.nlm.nih.gov/pubmed/36961981
http://dx.doi.org/10.1200/CCI.22.00181

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10530970/
https://www.ncbi.nlm.nih.gov/pubmed/36961981
http://dx.doi.org/10.1200/CCI.22.00181

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