AIMC Topic: Deep Learning

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Deep learning differentiates between healthy and diabetic mouse ears from optical coherence tomography angiography images.

Annals of the New York Academy of Sciences Feb 26, 2021
We trained a deep learning algorithm to use skin optical coherence tomography (OCT) angiograms to differentiate between healthy and type 2 diabetic mice. OCT angiograms were acquired with a custom-built OCT system based on an akinetic swept laser at ...
Mice Algorithms Diagnosis, Differential Tomography, Optical Coherence Female Deep Learning Reproducibility of Results Diabetes Mellitus, Experimental ROC Curve Image Processing, Computer-Assisted Angiography Machine Learning Animals Ear Case-Control Studies
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Deep Learning Whole-Gland and Zonal Prostate Segmentation on a Public MRI Dataset.

Journal of magnetic resonance imaging : JMRI Feb 26, 2021
BACKGROUND: Prostate volume, as determined by magnetic resonance imaging (MRI), is a useful biomarker both for distinguishing between benign and malignant pathology and can be used either alone or combined with other parameters such as prostate-speci...
Retrospective Studies Male Deep Learning Image Processing, Computer-Assisted Magnetic Resonance Imaging Prostatic Neoplasms Humans
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A fast saddle-point dynamical system approach to robust deep learning.

Neural networks : the official journal of the International Neural Network Society Feb 26, 2021
Recent focus on robustness to adversarial attacks for deep neural networks produced a large variety of algorithms for training robust models. Most of the effective algorithms involve solving the min-max optimization problem for training robust models...
Neural Networks, Computer Databases, Factual Algorithms Deep Learning Pattern Recognition, Automated
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Performance of a deep learning-based identification system for esophageal cancer from CT images.

Esophagus : official journal of the Japan Esophageal Society Feb 26, 2021
BACKGROUND: Because cancers of hollow organs such as the esophagus are hard to detect even by the expert physician, it is important to establish diagnostic systems to support physicians and increase the accuracy of diagnosis. In recent years, deep le...
Deep Learning Esophageal Neoplasms Retrospective Studies Tomography, X-Ray Computed Humans Artificial Intelligence
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Androgen Receptor Binding Category Prediction with Deep Neural Networks and Structure-, Ligand-, and Statistically Based Features.

Molecules (Basel, Switzerland) Feb 26, 2021
Substances that can modify the androgen receptor pathway in humans and animals are entering the environment and food chain with the proven ability to disrupt hormonal systems and leading to toxicity and adverse effects on reproduction, brain developm...
Humans Logistic Models Software Ligands Rats Neural Networks, Computer Algorithms Receptors, Androgen Proteins Deep Learning Animals Protein Binding
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Improved protein structure refinement guided by deep learning based accuracy estimation.

Nature communications Feb 26, 2021
We develop a deep learning framework (DeepAccNet) that estimates per-residue accuracy and residue-residue distance signed error in protein models and uses these predictions to guide Rosetta protein structure refinement. The network uses 3D convolutio...
Models, Molecular Models, Biological Caspases Protein Conformation Deep Learning Software Computational Biology Algorithms Proteins
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Robust and accurate decoding of hand kinematics from entire spiking activity using deep learning.

Journal of neural engineering Feb 26, 2021
. Brain-machine interfaces (BMIs) seek to restore lost motor functions in individuals with neurological disorders by enabling them to control external devices directly with their thoughts. This work aims to improve robustness and decoding accuracy th...
Deep Learning Brain-Computer Interfaces Motor Cortex Neural Networks, Computer Biomechanical Phenomena Animals
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A 2-year investigation of the impact of the computed tomography-derived fractional flow reserve calculated using a deep learning algorithm on routine decision-making for coronary artery disease management.

European radiology Feb 25, 2021
OBJECTIVE: This study aims to investigate the safety and feasibility of using a deep learning algorithm to calculate computed tomography angiography-based fractional flow reserve (DL-FFRCT) as an alternative to invasive coronary angiography (ICA) in ...
Humans Algorithms Retrospective Studies Coronary Angiography Coronary Artery Disease Computed Tomography Angiography Coronary Stenosis Fractional Flow Reserve, Myocardial Hemodynamics Tomography, X-Ray Computed Deep Learning Severity of Illness Index Predictive Value of Tests
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Using Deep Learning to Emulate the Use of an External Contrast Agent in Cardiovascular 4D Flow MRI.

Journal of magnetic resonance imaging : JMRI Feb 25, 2021
BACKGROUND: Although contrast agents would be beneficial, they are seldom used in four-dimensional (4D) flow magnetic resonance imaging (MRI) due to potential side effects and contraindications.
Contrast Media Magnetic Resonance Imaging Signal-To-Noise Ratio Retrospective Studies Deep Learning Humans
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Contrast agent dose reduction in computed tomography with deep learning using a conditional generative adversarial network.

European radiology Feb 25, 2021
OBJECTIVES: To reduce the dose of intravenous iodine-based contrast media (ICM) in CT through virtual contrast-enhanced images using generative adversarial networks.
Animals Deep Learning Image Processing, Computer-Assisted Humans Tomography, X-Ray Computed Contrast Media Signal-To-Noise Ratio Drug Tapering
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