AIMC Topic: Deep Learning

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Comparative effectiveness of convolutional neural network (CNN) and recurrent neural network (RNN) architectures for radiology text report classification.

Artificial intelligence in medicine Nov 23, 2018
This paper explores cutting-edge deep learning methods for information extraction from medical imaging free text reports at a multi-institutional scale and compares them to the state-of-the-art domain-specific rule-based system - PEFinder and traditi...
Pulmonary Embolism Information Storage and Retrieval Radiography, Thoracic Humans Neural Networks, Computer Deep Learning
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A feasibility study on an automated method to generate patient-specific dose distributions for radiotherapy using deep learning.

Medical physics Nov 23, 2018
PURPOSE: To develop a method for predicting optimal dose distributions, given the planning image and segmented anatomy, by applying deep learning techniques to a database of previously optimized and approved Intensity-modulated radiation therapy trea...
Humans Neural Networks, Computer Radiation Dosage Deep Learning Radiotherapy Dosage Radiotherapy, Intensity-Modulated Feasibility Studies Radiotherapy Planning, Computer-Assisted Automation
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DeepSeeNet: A Deep Learning Model for Automated Classification of Patient-based Age-related Macular Degeneration Severity from Color Fundus Photographs.

Ophthalmology Nov 22, 2018
PURPOSE: In assessing the severity of age-related macular degeneration (AMD), the Age-Related Eye Disease Study (AREDS) Simplified Severity Scale predicts the risk of progression to late AMD. However, its manual use requires the time-consuming partic...
Models, Theoretical Area Under Curve Diagnostic Techniques, Ophthalmological Photography Retinal Drusen Geographic Atrophy Severity of Illness Index Diagnosis, Computer-Assisted Deep Learning Male Middle Aged Disease Progression Female Reproducibility of Results Risk Factors Aged Aged, 80 and over Sensitivity and Specificity Humans Prospective Studies
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A picture tells a thousand…exposures: Opportunities and challenges of deep learning image analyses in exposure science and environmental epidemiology.

Environment international Nov 22, 2018
BACKGROUND: Artificial intelligence (AI) is revolutionizing our world, with applications ranging from medicine to engineering.
Humans Deep Learning Image Processing, Computer-Assisted Environmental Exposure Environmental Health
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Analysis of body pressure distribution on car seats by using deep learning.

Applied ergonomics Nov 21, 2018
This study aimed to extract information from body pressure distribution, including comfort, participant body size, and seat characteristics by using supervised deep learning, and body pressure characteristics corresponding to sensory evaluation by us...
Equipment Design Healthy Volunteers Pressure Ergonomics Male Humans Sitting Position Deep Learning Body Size Female Automobiles Adult
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Robot-Assisted Pedestrian Regulation Based on Deep Reinforcement Learning.

IEEE transactions on cybernetics Nov 20, 2018
Pedestrian regulation can prevent crowd accidents and improve crowd safety in densely populated areas. Recent studies use mobile robots to regulate pedestrian flows for desired collective motion through the effect of passive human-robot interaction (...
Crowding Image Processing, Computer-Assisted Humans Robotics Algorithms Pedestrians Deep Learning
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Adversarial MACE Prediction After Acute Coronary Syndrome Using Electronic Health Records.

IEEE journal of biomedical and health informatics Nov 20, 2018
Acute coronary syndrome (ACS), as an emergent and severe syndrome due to decreased blood flow in the coronary arteries, is a leading cause of death and serious long-term disability globally. ACS is usually caused by one of three problems: ST elevatio...
Deep Learning Models, Statistical Heart Failure Acute Coronary Syndrome Medical Informatics Aged Middle Aged Diagnosis, Computer-Assisted Humans Electronic Health Records
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Development and testing of a deep learning-based strategy for scar segmentation on CMR-LGE images.

Magma (New York, N.Y.) Nov 20, 2018
OBJECTIVE: The aim of this paper is to investigate the use of fully convolutional neural networks (FCNNs) to segment scar tissue in the left ventricle from cardiac magnetic resonance with late gadolinium enhancement (CMR-LGE) images.
Female Male Deep Learning Humans Neural Networks, Computer Retrospective Studies Heart Ventricles Gadolinium Image Enhancement Contrast Media Magnetic Resonance Imaging Cicatrix Myocardial Ischemia
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Deep learning in medical imaging and radiation therapy.

Medical physics Nov 20, 2018
The goals of this review paper on deep learning (DL) in medical imaging and radiation therapy are to (a) summarize what has been achieved to date; (b) identify common and unique challenges, and strategies that researchers have taken to address these ...
Humans Artifacts Deep Learning Signal-To-Noise Ratio Image Processing, Computer-Assisted Radiotherapy Diagnostic Imaging
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Bi-stream CNN Down Syndrome screening model based on genotyping array.

BMC medical genomics Nov 20, 2018
BACKGROUND: Human Down syndrome (DS) is usually caused by genomic micro-duplications and dosage imbalances of human chromosome 21. It is associated with many genomic and phenotype abnormalities. Even though human DS occurs about 1 per 1,000 births wo...
Down Syndrome Chromosome Mapping Humans Deep Learning Neural Networks, Computer Polymorphism, Single Nucleotide Genotype
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