Results 71 to 80 of about 852,410 (222)
Aging and Cancer, EarlyView.Aging weakens the blood–brain barrier (BBB), increasing susceptibility to CNS cancers and complicating treatment. This review examines BBB deterioration, its impact on drug delivery, and potential interventions like targeting neuroinflammation and advanced therapies.
Quang La, Aiman Baloch, David F. Lo
wiley +1 more source
Artificial neural networks and computer image analysis in the evaluation of selected quality parameters of pea seeds [PDF]
E3S Web of Conferences, 2019 The aim of the study was to develop an innovative method of modelling the process of evaluating the quality of agricultural crops on the basis of computer image analysis and artificial neural networks (ANN).
Szwedziak Katarzyna
doaj +1 more source
Neural Network Processing Neural Networks: An efficient way to learn higher order functions [PDF]
arXiv, 2019 Functions are rich in meaning and can be interpreted in a variety of ways. Neural networks were proven to be capable of approximating a large class of functions[1]. In this paper, we propose a new class of neural networks called "Neural Network Processing Neural Networks" (NNPNNs), which inputs neural networks and numerical values, instead of just ...
arxiv
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 +4 more
wiley +1 more source
Parametrical Neural Networks and Some Other Similar Architectures [PDF]
arXiv, 2006 A review of works on associative neural networks accomplished during last four years in the Institute of Optical Neural Technologies RAS is given. The presentation is based on description of parametrical neural networks (PNN). For today PNN have record recognizing characteristics (storage capacity, noise immunity and speed of operation).
arxiv
Journal of Applied Clinical Medical Physics, EarlyView.Abstract Current radiotherapy practices rely on manual contouring of CT scans, which is time‐consuming, prone to variability, and requires highly trained experts. There is a need for more efficient and consistent contouring methods. This study evaluated the performance of the Varian Ethos AI auto‐contouring tool to assess its potential integration into
Robert N. Finnegan +6 more
wiley +1 more source
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 +11 more
wiley +1 more source
One weird trick for parallelizing convolutional neural networks [PDF]
arXiv, 2014 I present a new way to parallelize the training of convolutional neural networks across multiple GPUs. The method scales significantly better than all alternatives when applied to modern convolutional neural networks.
arxiv
Are Deep Neural Networks "Robust"? [PDF]
arXiv, 2020 Separating outliers from inliers is the definition of robustness in computer vision. This essay delineates how deep neural networks are different than typical robust estimators. Deep neural networks not robust by this traditional definition.
arxiv
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 +2 more
wiley +1 more source