Results 81 to 90 of about 746,368 (310)

A review of artificial intelligence in brachytherapy

Journal of Applied Clinical Medical Physics, EarlyView.
Abstract Artificial intelligence (AI) has the potential to revolutionize brachytherapy's clinical workflow. This review comprehensively examines the application of AI, focusing on machine learning and deep learning, in various aspects of brachytherapy.
Jingchu Chen, Richard L. J. Qiu, Tonghe Wang, Shadab Momin, Xiaofeng Yang   +4 more
wiley   +1 more source

Convolution Forgetting Curve Model for Repeated Learning [PDF]

arXiv, 2019
Most of mathematic forgetting curve models fit well with the forgetting data under the learning condition of one time rather than repeated. In the paper, a convolution model of forgetting curve is proposed to simulate the memory process during learning. In this model, the memory ability (i.e.
arxiv  

Assessing HyperSight iterative CBCT for dose calculation in online adaptive radiotherapy for pelvis and breast patients compared to synthetic CT

Journal of Applied Clinical Medical Physics, EarlyView.
Abstract Purpose/objectives Recent technological advancements have increased efficiency for clinical deliverability of online‐adaptive‐radiotherapy (oART). Previous cone‐beam‐computed‐tomography (CBCT) generations lacked the ability to provide reliable Hounsfield‐units (HU), thus requiring oART workflows to rely on synthetic‐CT (sCT) images derived ...
Jingwei Duan, Joel A. Pogue, Dennis N. Stanley, Sui Shen, Natalie N. Viscariello, Carlos E. Cardenas, Richard A. Popple, Joseph Harms   +7 more
wiley   +1 more source

Classification of interest rate curves using Self-Organising Maps [PDF]

arXiv, 2007
The present study deals with the analysis and classification of interest rate curves. Interest rate curves (IRC) are the basic financial curves in many different fields of economics and finance. They are extremely important tools in banking and financial risk management problems.
arxiv  

Evaluating the use of diagnostic CT with flattening filter free beams for palliative radiotherapy: Dosimetric impact of scanner calibration variability

Journal of Applied Clinical Medical Physics, EarlyView.
Abstract Purpose Palliative radiotherapy comprises a significant portion of the radiation treatment workload. Volumetric‐modulated arc therapy (VMAT) improves dose conformity and, in conjunction with flattening filter free (FFF) delivery, can decrease treatment times, both of which are desirable in a population with a high probability of retreatment ...
Madeleine L. Van de Kleut, Lesley A. Buckley, Elsayed S. M. Ali   +2 more
wiley   +1 more source

W ciemnościach tunelu, 
czyli o zjawisku leksykalnego plateau

Postscriptum Polonistyczne, 2020
Level B (Independent user) is a specific stage in the process of language education because it consists of two completely different levels of language proficiency.
Anna Seretny
doaj  

Closed Curves and Elementary Visual Object Identification [PDF]

arXiv, 2015
For two closed curves on a plane (discrete version) and local criteria for similarity of points on the curves one gets a potential, which describes the similarity between curve points. This is the base for a global similarity measure of closed curves (Fr\'echet distance). I use borderlines of handwritten digits to demonstrate an area of application.
arxiv  

Closing the gap in plan quality: Leveraging deep‐learning dose prediction for adaptive radiotherapy

Journal of Applied Clinical Medical Physics, EarlyView.
Abstract Purpose Balancing quality and efficiency has been a challenge for online adaptive therapy. Most systems start the online re‐optimization with the original planning goals. While some systems allow planners to modify the planning goals, achieving a high‐quality plan within time constraints remains a common barrier.
Sean J. Domal, Austen Maniscalco, Justin Visak, Michael Dohopolski, Dominic Moon, Vladimir Avkshtol, Dan Nguyen, Steve Jiang, David Sher, Mu‐ Han Lin   +9 more
wiley   +1 more source

Gaussian Process Regression with Mismatched Models [PDF]

arXiv, 2001
Learning curves for Gaussian process regression are well understood when the `student' model happens to match the `teacher' (true data generation process). I derive approximations to the learning curves for the more generic case of mismatched models, and find very rich behaviour: For large input space dimensionality, where the results become exact ...
arxiv  

A comparative analysis of deep learning architectures with data augmentation and multichannel input for locoregional breast cancer radiotherapy

Journal of Applied Clinical Medical Physics, EarlyView.
Abstract Purpose Studies on deep learning dose prediction increasingly focus on 3D models with multiple input channels and data augmentation, which increases the training time and thus also the environmental burden and hampers the ease of re‐training. Here we compare 2D and 3D U‐Net models with clinical accepted plans to evaluate the appropriateness of
Rosalie Klarenberg, Nienke L. M. Bakx, Coen W. Hurkmans   +2 more
wiley   +1 more source