Cargando…
A machine learning based delta-radiomics process for early prediction of treatment response of pancreatic cancer
Changes of radiomic features over time in longitudinal images, delta radiomics, can potentially be used as a biomarker to predict treatment response. This study aims to develop a delta-radiomic process based on machine learning by (1) acquiring and registering longitudinal images, (2) segmenting and...
Autores principales: | Nasief, Haidy, Zheng, Cheng, Schott, Diane, Hall, William, Tsai, Susan, Erickson, Beth, Allen Li, X. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6778189/ https://www.ncbi.nlm.nih.gov/pubmed/31602401 http://dx.doi.org/10.1038/s41698-019-0096-z |
Ejemplares similares
-
Improving Treatment Response Prediction for Chemoradiation Therapy of Pancreatic Cancer Using a Combination of Delta-Radiomics and the Clinical Biomarker CA19-9
por: Nasief, Haidy, et al.
Publicado: (2020) -
Assessment of treatment response during chemoradiation therapy for pancreatic cancer based on quantitative radiomic analysis of daily CTs: An exploratory study
por: Chen, Xiaojian, et al.
Publicado: (2017) -
An investigation of machine learning methods in delta-radiomics feature analysis
por: Chang, Yushi, et al.
Publicado: (2019) -
Correlation of ADC With Pathological Treatment Response for Radiation Therapy of Pancreatic Cancer
por: Dalah, Entesar, et al.
Publicado: (2018) -
The CT delta-radiomics based machine learning approach in evaluating multiple primary lung adenocarcinoma
por: Ma, Yanqing, et al.
Publicado: (2022)