Cargando…
Prediction of chemotherapy response in breast cancer patients at pre-treatment using second derivative texture of CT images and machine learning
Although neoadjuvant chemotherapy (NAC) is a crucial component of treatment for locally advanced breast cancer (LABC), only about 70% of patients respond to it. Effective adjustment of NAC for individual patients can significantly improve survival rates of those resistant to standard regimens. Thus,...
Autores principales: | Moghadas-Dastjerdi, Hadi, Rahman, Shan-E-Tallat Hira, Sannachi, Lakshmanan, Wright, Frances C., Gandhi, Sonal, Trudeau, Maureen E., Sadeghi-Naini, Ali, Czarnota, Gregory J. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Neoplasia Press
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8319580/ https://www.ncbi.nlm.nih.gov/pubmed/34293685 http://dx.doi.org/10.1016/j.tranon.2021.101183 |
Ejemplares similares
-
A priori prediction of tumour response to neoadjuvant chemotherapy in breast cancer patients using quantitative CT and machine learning
por: Moghadas-Dastjerdi, Hadi, et al.
Publicado: (2020) -
Early prediction of therapy responses and outcomes in breast cancer patients using quantitative ultrasound spectral texture
por: Sadeghi-Naini, Ali, et al.
Publicado: (2014) -
Response monitoring of breast cancer patients receiving neoadjuvant chemotherapy using quantitative ultrasound, texture, and molecular features
por: Sannachi, Lakshmanan, et al.
Publicado: (2018) -
Breast Cancer Treatment Response Monitoring Using Quantitative Ultrasound and Texture Analysis: Comparative Analysis of Analytical Models
por: Sannachi, Lakshmanan, et al.
Publicado: (2019) -
Chemotherapy-Response Monitoring of Breast Cancer Patients Using Quantitative Ultrasound-Based Intra-Tumour Heterogeneities
por: Sadeghi-Naini, Ali, et al.
Publicado: (2017)