Predicting Underestimation of Invasive Cancer in Patients with Core-Needle-Biopsy-Diagnosed Ductal Carcinoma In Situ Using Deep Learning Algorithms

The prediction of an occult invasive component in ductal carcinoma in situ (DCIS) before surgery is of clinical importance because the treatment strategies are different between pure DCIS without invasive component and upgraded DCIS. We demonstrated the potential of using deep learning models for di...

Descripción completa

Detalles Bibliográficos
Autores principales: Do, Luu-Ngoc, Lee, Hyo-Jae, Im, Chaeyeong, Park, Jae Hyeok, Lim, Hyo Soon, Park, Ilwoo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9844271/
https://www.ncbi.nlm.nih.gov/pubmed/36648988
http://dx.doi.org/10.3390/tomography9010001

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9844271/
https://www.ncbi.nlm.nih.gov/pubmed/36648988
http://dx.doi.org/10.3390/tomography9010001

Ejemplares similares