Bias and class imbalance in oncologic data—towards inclusive and transferrable AI in large scale oncology data sets
Simple Summary Large-scale medical data carries significant areas of underrepresentation
and bias at all levels: clinical, biological, and management. Resulting data sets and outcome …
and bias at all levels: clinical, biological, and management. Resulting data sets and outcome …
Knowledge‐based planning for intensity‐modulated radiation therapy: a review of data‐driven approaches
Y Ge, QJ Wu - Medical physics, 2019 - Wiley Online Library
Purpose Intensity‐Modulated Radiation Therapy (IMRT), including its variations (including
IMRT, Volumetric Arc Therapy (VMAT), and Tomotherapy), is a widely used and critically …
IMRT, Volumetric Arc Therapy (VMAT), and Tomotherapy), is a widely used and critically …
Real-value negative selection over-sampling for imbalanced data set learning
X Tao, Q Li, C Ren, W Guo, C Li, Q He, R Liu… - Expert Systems with …, 2019 - Elsevier
The learning problem from imbalanced data set poses a major challenge in data mining
community. Conventional machine learning algorithms show poor performance in dealing …
community. Conventional machine learning algorithms show poor performance in dealing …
Machine learning for automated quality assurance in radiotherapy: A proof of principle using EPID data description
Purpose Developing automated methods to identify task‐driven quality assurance (QA)
procedures is key toward increasing safety, efficacy, and efficiency. We investigate the use …
procedures is key toward increasing safety, efficacy, and efficiency. We investigate the use …
Using artificial intelligence to improve the quality and safety of radiation therapy
Within artificial intelligence, machine learning (ML) efforts in radiation oncology have
augmented the transition from generalized to personalized treatment delivery. Although their …
augmented the transition from generalized to personalized treatment delivery. Although their …
[HTML][HTML] Artificial intelligence in radiation oncology treatment planning: a brief overview
KJ Kiser, CD Fuller, VK Reed - Journal of Medical Artificial …, 2019 - jmai.amegroups.org
Among medical specialties, radiation oncology has long been an innovator and early
adopter of therapeutic technologies. This specialty is now situated in prime position to be …
adopter of therapeutic technologies. This specialty is now situated in prime position to be …
Characterization of a Bayesian network‐based radiotherapy plan verification model
Purpose The current process for radiotherapy treatment plan quality assurance relies on
human inspection of treatment plans, which is time‐consuming, error prone and oft reliant on …
human inspection of treatment plans, which is time‐consuming, error prone and oft reliant on …
Understanding machine learning classifier decisions in automated radiotherapy quality assurance
The complexity of generating radiotherapy treatments demands a rigorous quality assurance
(QA) process to ensure patient safety and to avoid clinically significant errors. Machine …
(QA) process to ensure patient safety and to avoid clinically significant errors. Machine …
Feature engineering for interpretable machine learning for quality assurance in radiation oncology
Chart checking is a time intensive process with high cognitive workload for physicists.
Previous studies have partially automated and standardized chart checking, but limited …
Previous studies have partially automated and standardized chart checking, but limited …
A Rule-Based Approach for Interpretable Intensity-Modulated Radiation Therapy Treatment Selection
X Gonzalez-Garcia, J Fumanal-Idocin… - … on Fuzzy Systems …, 2024 - ieeexplore.ieee.org
Artificial Intelligence (AI) methods are becoming essential in healthcare. In the context of
Intensity-Modulated Radiation Therapy (IMRT), Knowledge-Based Planning (KBP) …
Intensity-Modulated Radiation Therapy (IMRT), Knowledge-Based Planning (KBP) …