AIMC Topic: Datasets as Topic

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Methodological Advances in the Study of Hidden Variables: A Demonstration on Clinical Alcohol Use Disorder Data.

AMIA ... Annual Symposium proceedings. AMIA Symposium Dec 5, 2018
Research in the domain of psychopathology has been hindered by hidden variables-variables that are important to understanding and treating psychopathological illnesses but are unmeasured. Recent methodological advances in machine learning have culmin...
Datasets as Topic Alcoholism Humans Psychopathology Algorithms Data Interpretation, Statistical
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Learning to Personalize from Practice: A Real World Evidence Approach of Care Plan Personalization based on Differential Patient Behavioral Responses in Care Management Records.

AMIA ... Annual Symposium proceedings. AMIA Symposium Dec 5, 2018
Recent studies documented the importance of individuality and heterogeneity in care planning. In practice, varying behavioral responses are revealed in patients' care management (CM) records. However, today's care programs are structured around popul...
Humans Medical Records Machine Learning Patient Care Management Behavior Precision Medicine Decision Making Patient Care Planning Patient-Centered Care 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...
Datasets as Topic Spectrum Analysis Regression Analysis Hemoglobins Video Recording Humans Neural Networks, Computer Female Young Adult Sensitivity and Specificity Middle Aged Adult Male Smartphone
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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...
Adult Middle Aged Deep Learning Aged Aged, 80 and over Young Adult Neuroimaging Neuroanatomy Image Processing, Computer-Assisted Magnetic Resonance Imaging Datasets as Topic Neural Networks, Computer Brain 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 Molecular Dynamics Simulation Nucleic Acid Conformation RNA Monte Carlo Method Datasets as Topic Hot Temperature
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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...
Image Interpretation, Computer-Assisted Artifacts Female Datasets as Topic Infant, Newborn Supervised Machine Learning Image Processing, Computer-Assisted Male Humans Quality Control Magnetic Resonance Imaging
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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 ...
Critical Care Datasets as Topic APACHE Patient Admission Decision Support Systems, Clinical Logistic Models Feasibility Studies Sepsis Hospital Mortality ROC Curve Intensive Care Units Machine Learning Clinical Decision-Making Prognosis Female Humans Retrospective Studies Middle Aged Risk Assessment Aged Male
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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...
Neural Networks, Computer Machine Learning Algorithms Datasets as Topic Brain-Computer Interfaces Learning Electroencephalography Humans Evoked Potentials, Motor Imagery, Psychotherapy
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