Cargando…
CT-based radiomics model with machine learning for predicting primary treatment failure in diffuse large B-cell Lymphoma
Biomarkers which can identify Diffuse Large B-Cell Lymphoma (DLBCL) likely to be refractory to first-line therapy are essential for selecting this population prior to therapy initiation to offer alternate therapeutic options that can improve prognosis. We tested the ability of a CT-based radiomics a...
Autores principales: | Santiago, Raoul, Ortiz Jimenez, Johanna, Forghani, Reza, Muthukrishnan, Nikesh, Del Corpo, Olivier, Karthigesu, Shairabi, Haider, Muhammad Yahya, Reinhold, Caroline, Assouline, Sarit |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Neoplasia Press
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8348197/ https://www.ncbi.nlm.nih.gov/pubmed/34343854 http://dx.doi.org/10.1016/j.tranon.2021.101188 |
Ejemplares similares
-
Radiomics and Artificial Intelligence for Biomarker and Prediction Model Development in Oncology
por: Forghani, Reza, et al.
Publicado: (2019) -
Radiomics and machine learning for the diagnosis of pediatric cervical non-tuberculous mycobacterial lymphadenitis
por: Al Bulushi, Yarab, et al.
Publicado: (2022) -
Dual-Energy CT Texture Analysis With Machine Learning for the Evaluation and Characterization of Cervical Lymphadenopathy
por: Seidler, Matthew, et al.
Publicado: (2019) -
Site-Specific Variation in Radiomic Features of Head and Neck Squamous Cell Carcinoma and Its Impact on Machine Learning Models
por: Liu, Xiaoyang, et al.
Publicado: (2021) -
Baseline (18)F-FDG PET/CT radiomics for prognosis prediction in diffuse large B cell lymphoma
por: Jing, Fenglian, et al.
Publicado: (2023)