AIMC Topic: Datasets as Topic

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SmartHeLP: Smartphone-based Hemoglobin Level Prediction Using an Artificial Neural Network.

AMIA ... Annual Symposium proceedings. AMIA Symposium Dec 5, 2018
Blood hemoglobin level (Hgb) measurement has a vital role in the diagnosis, evaluation, and management of numerous diseases. We describe the use of smartphone video imaging and an artificial neural network (ANN) system to estimate Hgb levels non-inva...
Male Middle Aged Smartphone Video Recording Spectrum Analysis Datasets as Topic Young Adult Humans Adult Neural Networks, Computer Sensitivity and Specificity Female Regression Analysis Hemoglobins
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QuickNAT: A fully convolutional network for quick and accurate segmentation of neuroanatomy.

NeuroImage Nov 29, 2018
Whole brain segmentation from structural magnetic resonance imaging (MRI) is a prerequisite for most morphological analyses, but is computationally intense and can therefore delay the availability of image markers after scan acquisition. We introduce...
Aged, 80 and over Young Adult Adult Middle Aged Neural Networks, Computer Brain Aged Datasets as Topic Neuroimaging Neuroanatomy Deep Learning Image Processing, Computer-Assisted Magnetic Resonance Imaging Humans
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RNA3DCNN: Local and global quality assessments of RNA 3D structures using 3D deep convolutional neural networks.

PLoS computational biology Nov 27, 2018
Quality assessment is essential for the computational prediction and design of RNA tertiary structures. To date, several knowledge-based statistical potentials have been proposed and proved to be effective in identifying native and near-native RNA st...
Neural Networks, Computer Hot Temperature Nucleic Acid Conformation Monte Carlo Method Molecular Dynamics Simulation RNA Datasets as Topic
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Supervised machine learning quality control for magnetic resonance artifacts in neonatal data sets.

Human brain mapping Nov 22, 2018
Quality control (QC) of brain magnetic resonance images (MRI) is an important process requiring a significant amount of manual inspection. Major artifacts, such as severe subject motion, are easy to identify to naïve observers but lack automated iden...
Humans Female Infant, Newborn Magnetic Resonance Imaging Datasets as Topic Quality Control Male Image Interpretation, Computer-Assisted Image Processing, Computer-Assisted Supervised Machine Learning Artifacts
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Optimal intensive care outcome prediction over time using machine learning.

PloS one Nov 14, 2018
BACKGROUND: Prognostication is an essential tool for risk adjustment and decision making in the intensive care unit (ICU). Research into prognostication in ICU has so far been limited to data from admission or the first 24 hours. Most ICU admissions ...
Male Middle Aged Risk Assessment ROC Curve Decision Support Systems, Clinical Sepsis Hospital Mortality Clinical Decision-Making Prognosis Datasets as Topic Humans Female APACHE Logistic Models Retrospective Studies Machine Learning Aged Patient Admission Intensive Care Units Feasibility Studies Critical Care
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Computer vs human: Deep learning versus perceptual training for the detection of neck of femur fractures.

Journal of medical imaging and radiation oncology Nov 8, 2018
INTRODUCTION: To evaluate the accuracy of deep convolutional neural networks (DCNNs) for detecting neck of femur (NoF) fractures on radiographs, in comparison with perceptual training in medically-naïve individuals.
Neural Networks, Computer Deep Learning Femoral Neck Fractures Datasets as Topic Humans
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The generalisability of artificial neural networks used to classify electrophoretic data produced under different conditions.

Forensic science international. Genetics Nov 2, 2018
Previous work has shown that artificial neural networks can be used to classify signal in an electropherogram into categories that have interpretational meaning (such as allele, baseline, pull-up or stutter). The previous work trained the neural netw...
Humans Neural Networks, Computer Electrophoresis Datasets as Topic Forensic Genetics
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Sparse Representation-Based Extreme Learning Machine for Motor Imagery EEG Classification.

Computational intelligence and neuroscience Oct 28, 2018
Classification of motor imagery (MI) electroencephalogram (EEG) plays a vital role in brain-computer interface (BCI) systems. Recent research has shown that nonlinear classification algorithms perform better than their linear counterparts, but most o...
Machine Learning Algorithms Learning Humans Neural Networks, Computer Evoked Potentials, Motor Electroencephalography Imagery, Psychotherapy Datasets as Topic Brain-Computer Interfaces
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Prediction and functional analysis of prokaryote lysine acetylation site by incorporating six types of features into Chou's general PseAAC.

Journal of theoretical biology Oct 23, 2018
Lysine acetylation is one of the most important types of protein post-translational modifications (PTM) that are widely involved in cellular regulatory processes. To fully understand the regulatory mechanism of acetylation, identification of acetylat...
Lysine Binding Sites Prokaryotic Cells Computational Biology Support Vector Machine Protein Processing, Post-Translational Bacteria Species Specificity Bacterial Proteins Acetylation Datasets as Topic
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Diagnostic accuracy of content-based dermatoscopic image retrieval with deep classification features.

The British journal of dermatology Oct 17, 2018
BACKGROUND: Automated classification of medical images through neural networks can reach high accuracy rates but lacks interpretability.
Deep Learning ROC Curve Image Processing, Computer-Assisted Datasets as Topic Skin Skin Diseases Humans Retrospective Studies Dermoscopy
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