Cargando…
A Super-Learner Model for Tumor Motion Prediction and Management in Radiation Therapy: Development and Feasibility Evaluation
In cancer radiation therapy, large tumor motion due to respiration can lead to uncertainties in tumor target delineation and treatment delivery, thus making active motion management an essential step in thoracic and abdominal tumor treatment. In current practice, patients with tumor motion may be re...
Autores principales: | Lin, Hui, Zou, Wei, Li, Taoran, Feigenberg, Steven J., Teo, Boon-Keng K., Dong, Lei |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6795883/ https://www.ncbi.nlm.nih.gov/pubmed/31619736 http://dx.doi.org/10.1038/s41598-019-51338-y |
Ejemplares similares
-
Higher Dose Volumes May Be Better for Evaluating Radiation Pneumonitis in Lung Proton Therapy Patients Compared With Traditional Photon-Based Dose Constraints
por: Harris, Wendy B., et al.
Publicado: (2020) -
Characterization of the Megavoltage Cone-Beam Computed Tomography (MV-CBCT) System on Halcyon(TM) for IGRT: Image Quality Benchmark, Clinical Performance, and Organ Doses
por: Malajovich, Irina, et al.
Publicado: (2019) -
A SuperLearner Approach to Predict Run-In Selection in Clinical Trials
por: Lanera, Corrado, et al.
Publicado: (2022) -
Predicting cumulative lead (Pb) exposure using the Super Learner algorithm
por: Wang, Xin, et al.
Publicado: (2023) -
Dosimetric Performance and Planning/Delivery Efficiency of a Dual-Layer Stacked and Staggered MLC on Treating Multiple Small Targets: A Planning Study Based on Single-Isocenter Multi-Target Stereotactic Radiosurgery (SRS) to Brain Metastases
por: Li, Taoran, et al.
Publicado: (2019)