AIMC Topic:
Computer Simulation

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Fidelity imposed network edit (FINE) for solving ill-posed image reconstruction.

NeuroImage Jan 22, 2020
Deep learning (DL) is increasingly used to solve ill-posed inverse problems in medical imaging, such as reconstruction from noisy and/or incomplete data, as DL offers advantages over conventional methods that rely on explicit image features and hand ...
Adult Deep Learning Image Processing, Computer-Assisted Magnetic Resonance Imaging Humans Neuroimaging Cerebral Hemorrhage Brain Multiple Sclerosis Computer Simulation
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And the nominees are: Using design-awards datasets to build computational aesthetic evaluation model.

PloS one Jan 21, 2020
Aesthetic perception is a human instinct that is responsive to multimedia stimuli. Giving computers the ability to assess human sensory and perceptual experience of aesthetics is a well-recognized need for the intelligent design industry and multimed...
Esthetics Awards and Prizes Image Processing, Computer-Assisted Equipment Design Datasets as Topic Machine Learning Humans Computer Simulation
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Validating the validation: reanalyzing a large-scale comparison of deep learning and machine learning models for bioactivity prediction.

Journal of computer-aided molecular design Jan 20, 2020
Machine learning methods may have the potential to significantly accelerate drug discovery. However, the increasing rate of new methodological approaches being published in the literature raises the fundamental question of how models should be benchm...
Machine Learning Algorithms Computer Simulation User-Computer Interface ROC Curve Drug Evaluation, Preclinical Drug Discovery Humans Deep Learning Support Vector Machine Area Under Curve Benchmarking
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Stochastic rounding and reduced-precision fixed-point arithmetic for solving neural ordinary differential equations.

Philosophical transactions. Series A, Mathematical, physical, and engineering sciences Jan 20, 2020
Although double-precision floating-point arithmetic currently dominates high-performance computing, there is increasing interest in smaller and simpler arithmetic types. The main reasons are potential improvements in energy efficiency and memory foot...
Software Stochastic Processes Models, Neurological Humans Algorithms Action Potentials Machine Learning Computer Simulation
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Rethinking arithmetic for deep neural networks.

Philosophical transactions. Series A, Mathematical, physical, and engineering sciences Jan 20, 2020
We consider efficiency in the implementation of deep neural networks. Hardware accelerators are gaining interest as machine learning becomes one of the drivers of high-performance computing. In these accelerators, the directed graph describing a neur...
Electronics Logic Algorithms Computer Simulation Deep Learning Neural Networks, Computer
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A Deep Learning Framework for Assessing Physical Rehabilitation Exercises.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Jan 13, 2020
Computer-aided assessment of physical rehabilitation entails evaluation of patient performance in completing prescribed rehabilitation exercises, based on processing movement data captured with a sensory system. Despite the essential role of rehabili...
Normal Distribution Movement Rehabilitation Exercise Therapy Healthy Volunteers Automation Neural Networks, Computer Algorithms Computer Simulation Biomechanical Phenomena Deep Learning Treatment Outcome Humans
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Machine learning derived input-function in a dynamic F-FDG PET study of mice.

Biomedical physics & engineering express Jan 13, 2020
Tracer kinetic modelling, based on dynamic F-fluorodeoxyglucose (FDG) positron emission tomography (PET) is used to quantify glucose metabolism in humans and animals. Knowledge of the arterial input-function (AIF) is required for such measurements. O...
Mice, Inbred BALB C Female Machine Learning Image Interpretation, Computer-Assisted Animals Radiopharmaceuticals Fluorodeoxyglucose F18 Algorithms Mice Arteries Positron-Emission Tomography Computer Simulation
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In silico spectral libraries by deep learning facilitate data-independent acquisition proteomics.

Nature communications Jan 9, 2020
Data-independent acquisition (DIA) is an emerging technology for quantitative proteomic analysis of large cohorts of samples. However, sample-specific spectral libraries built by data-dependent acquisition (DDA) experiments are required prior to DIA ...
Databases, Protein Peptides Humans Peptide Library HeLa Cells Cell Line, Tumor Deep Learning Computer Simulation Computational Biology Mice Serum Proteomics Data Science Animals Proteome Mass Spectrometry
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Training and Validation of Deep Neural Networks for the Prediction of 90-Day Post-Liver Transplant Mortality Using UNOS Registry Data.

Transplantation proceedings Jan 8, 2020
Prediction models of post-liver transplant mortality are crucial so that donor organs are not allocated to recipients with unreasonably high probabilities of mortality. Machine learning algorithms, particularly deep neural networks (DNNs), can often ...
Adult Male Deep Learning ROC Curve Humans Computer Simulation Female Living Donors Registries Liver Transplantation
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Crowding reveals fundamental differences in local vs. global processing in humans and machines.

Vision research Jan 7, 2020
Feedforward Convolutional Neural Networks (ffCNNs) have become state-of-the-art models both in computer vision and neuroscience. However, human-like performance of ffCNNs does not necessarily imply human-like computations. Previous studies have sugge...
Image Processing, Computer-Assisted Vision, Ocular Humans Crowding Neural Networks, Computer Form Perception Computer Simulation
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