Results 211 to 220 of about 3,295,261 (308)

Toward a human‐centric co‐design methodology for AI detection of differences between planned and delivered dose in radiotherapy

Journal of Applied Clinical Medical Physics, EarlyView.
Abstract Introduction Many artificial intelligence (AI) solutions have been proposed to enhance the radiotherapy (RT) workflow, but limited applications have been implemented to date, suggesting an implementation gap. One contributing factor to this gap is a misalignment between AI systems and their users.
Luca M. Heising, Frank Verhaegen, Stefan G. Scheib, Maria J. G. Jacobs, Carol X. J. Ou, Viola Mottarella, Yin‐Ho Chong, Mariangela Zamburlini, Sebastiaan M. J. J. G. Nijsten, Ans Swinnen, Michel Öllers, Cecile J. A. Wolfs   +11 more
wiley   +1 more source

Detectability constraints on meso-scale structure in complex networks. [PDF]

PLoS One
Arthur R.
europepmc   +1 more source

A Python package for fast GPU‐based proton pencil beam dose calculation

Journal of Applied Clinical Medical Physics, EarlyView.
Abstract Purpose Open‐source GPU‐based Monte Carlo (MC) proton dose calculation algorithms provide high speed and unparalleled accuracy but can be complex to integrate with new applications and remain slower than GPU‐based pencil beam (PB) methods, which sacrifice some physical accuracy for sub‐second plan calculation.
Mahasweta Bhattacharya, Calin Reamy, Heng Li, Junghoon Lee, William T. Hrinivich   +4 more
wiley   +1 more source

Frustrated Synchronization of the Kuramoto Model on Complex Networks. [PDF]

Entropy (Basel)
Ódor G, Deng S, Kelling J.
europepmc   +1 more source

Exploring the Entropy Complex Networks with Latent Interaction. [PDF]

Entropy (Basel), 2023
Centeno Mejia AA, Bravo Gaete MF.
europepmc   +1 more source

Risk analysis of the Unity 1.5T MR‐Linac adapt‐to‐shape workflow

Journal of Applied Clinical Medical Physics, EarlyView.
Abstract Background and Purpose The adapt‐to‐shape (ATS) workflow on the Unity MR‐Linac (Elekta AB, Stockholm, Sweden) allows for full replanning including recontouring and reoptimization5. Additional complexity to this workflow is added when the adaptation involves the use of MIM Maestro (MIM Software, Cleveland, OH) software in conjunction with ...
Jiayi Liang, Eric Aliotta, Neelam Tyagi, Paola Godoy Scripes, Nicolas Côté, Ergys Subashi, Qijie Huang, Lian Sun, Ching‐Yun Chan, Angela Ng, Theresa Wunner, Victoria Brennan, Kaveh Zakeri, James Mechalakos   +13 more
wiley   +1 more source

Causal interaction of metabolic oscillations in monolayers of Hela cervical cancer cells: emergence of complex networks. [PDF]

Sci Rep
Amemiya T, Shuto S, Fujita I, Shibata K, Nakamura K, Watanabe M, Yamaguchi T.   +6 more
europepmc   +1 more source

Unsupervised non‐small cell lung cancer tumor segmentation using cycled generative adversarial network with similarity‐based discriminator

Journal of Applied Clinical Medical Physics, EarlyView.
Abstract Background Tumor segmentation is crucial for lung disease diagnosis and treatment. Most existing deep learning‐based automatic segmentation methods rely on manually annotated data for network training. Purpose This study aims to develop an unsupervised tumor segmentation network smic‐GAN by using a similarity‐driven generative adversarial ...
Chengyijue Fang, Xiaoyang Li, Yidong Yang   +2 more
wiley   +1 more source

Detailed-level modelling of influence spreading on complex networks. [PDF]

Sci Rep
Kuikka V, Kaski KK.
europepmc   +1 more source

Scaling laws of failure dynamics on complex networks. [PDF]

Sci Rep, 2023
Pál G, Danku Z, Batool A, Kádár V, Yoshioka N, Ito N, Ódor G, Kun F.   +7 more
europepmc   +1 more source