Artificial intelligence in radiotherapy
G Li, X Wu, X Ma - Seminars in Cancer Biology, 2022 - Elsevier
Radiotherapy is a discipline closely integrated with computer science. Artificial intelligence
(AI) has developed rapidly over the past few years. With the explosive growth of medical big …
(AI) has developed rapidly over the past few years. With the explosive growth of medical big …
Integration of AI and machine learning in radiotherapy QA
The use of machine learning and other sophisticated models to aid in prediction and
decision making has become widely popular across a breadth of disciplines. Within the …
decision making has become widely popular across a breadth of disciplines. Within the …
Hybrid deep learning for botnet attack detection in the internet-of-things networks
Deep learning (DL) is an efficient method for botnet attack detection. However, the volume of
network traffic data and memory space required is usually large. It is, therefore, almost …
network traffic data and memory space required is usually large. It is, therefore, almost …
Towards a safe and efficient clinical implementation of machine learning in radiation oncology by exploring model interpretability, explainability and data-model …
A Barragán-Montero, A Bibal… - Physics in Medicine …, 2022 - iopscience.iop.org
The interest in machine learning (ML) has grown tremendously in recent years, partly due to
the performance leap that occurred with new techniques of deep learning, convolutional …
the performance leap that occurred with new techniques of deep learning, convolutional …
Applications of machine and deep learning to patient‐specific IMRT/VMAT quality assurance
In order to deliver accurate and safe treatment to cancer patients in radiation therapy using
advanced techniques such as intensity modulated radiation therapy (IMRT) and volumetric …
advanced techniques such as intensity modulated radiation therapy (IMRT) and volumetric …
Improving the quality of care in radiation oncology using artificial intelligence
Radiation therapy is a complex process involving multiple professionals and steps from
simulation to treatment planning to delivery, and these procedures are prone to error …
simulation to treatment planning to delivery, and these procedures are prone to error …
Artificial Intelligence in radiotherapy: state of the art and future directions
G Francolini, I Desideri, G Stocchi, V Salvestrini… - Medical Oncology, 2020 - Springer
Recent advances in computing capability allowed the development of sophisticated
predictive models to assess complex relationships within observational data, described as …
predictive models to assess complex relationships within observational data, described as …
Systematic method for a deep learning‐based prediction model for gamma evaluation in patient‐specific quality assurance of volumetric modulated arc therapy
S Tomori, N Kadoya, T Kajikawa, Y Kimura… - Medical …, 2021 - Wiley Online Library
Purpose This study aimed to develop and evaluate a novel strategy for establishing a deep
learning‐based gamma passing rate (GPR) prediction model for volumetric modulated arc …
learning‐based gamma passing rate (GPR) prediction model for volumetric modulated arc …
A tool for patient‐specific prediction of delivery discrepancies in machine parameters using trajectory log files
Purpose Multileaf collimator (MLC) delivery discrepancy between planned and actual
(delivered) positions have detrimental effect on the accuracy of dose distributions for both …
(delivered) positions have detrimental effect on the accuracy of dose distributions for both …
A synthesized gamma distribution‐based patient‐specific VMAT QA using a generative adversarial network
T Matsuura, D Kawahara, A Saito, K Yamada… - Medical …, 2023 - Wiley Online Library
Background Artificial intelligence (AI)‐based gamma passing rate (GPR) prediction has
been proposed as a time‐efficient virtual patient‐specific QA method for the delivery of …
been proposed as a time‐efficient virtual patient‐specific QA method for the delivery of …