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In Vivo Dosimetry

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Predictive time-series modeling using artificial neural networks for Linac beam symmetry: an empirical study.

Annals of the New York Academy of Sciences 27627049
Over half of cancer patients receive radiotherapy (RT) as partial or full cancer treatment. Daily quality assurance (QA) of RT in cancer treatment closely monitors the performance of the medical linear accelerator (Linac) and is critical for continuo...
Bayes Theorem Computational Biology Databases, Factual Empirical Research Forecasting Humans In Vivo Dosimetry Kinetics Longitudinal Studies Machine Learning Models, Biological Neoplasms Neural Networks, Computer Quality Assurance, Health Care Radiosurgery Regression Analysis Reproducibility of Results
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Prediction of skin dose in low-kV intraoperative radiotherapy using machine learning models trained on results of in vivo dosimetry.

Medical physics 30620412
PURPOSE: The purpose of this study was to implement a machine learning model to predict skin dose from targeted intraoperative (TARGIT) treatment resulting in timely adoption of strategies to limit excessive skin dose.
Adult Aged Aged, 80 and over Breast Neoplasms Female Humans In Vivo Dosimetry Intraoperative Care Machine Learning Mastectomy, Segmental Middle Aged Models, Statistical Neural Networks, Computer Organs at Risk Radiotherapy Dosage Skin
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Deep learning-based tools to distinguish plan-specific from generic deviations in EPID-based in vivo dosimetry.

Medical physics 38112213
BACKGROUND: Dose distributions calculated with electronic portal imaging device (EPID)-based in vivo dosimetry (EIVD) differ from planned dose distributions due to generic and plan-specific deviations. Generic deviations are characteristic to a class...
Deep Learning Humans In Vivo Dosimetry Male Radiometry Radiotherapy Dosage Radiotherapy Planning, Computer-Assisted Radiotherapy, Intensity-Modulated
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