AIMC Topic: Adult

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Using neuroimaging to predict relapse in stimulant dependence: A comparison of linear and machine learning models.

NeuroImage. Clinical Jan 11, 2019
OBJECTIVE: Relapse rates are consistently high for stimulant user disorders. In order to obtain prognostic information about individuals in treatment, machine learning models have been applied to neuroimaging and clinical data. Yet few efforts have b...
Depressive Disorder, Major ROC Curve Logistic Models Longitudinal Studies Methamphetamine Machine Learning Female Neuroimaging Adult Recurrence Male Humans
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EEG-Based Spatio-Temporal Convolutional Neural Network for Driver Fatigue Evaluation.

IEEE transactions on neural networks and learning systems Jan 10, 2019
Driver fatigue evaluation is of great importance for traffic safety and many intricate factors would exacerbate the difficulty. In this paper, based on the spatial-temporal structure of multichannel electroencephalogram (EEG) signals, we develop a no...
Female Young Adult Photic Stimulation Humans Adult Neural Networks, Computer Male Time Factors Virtual Reality Electroencephalography Automobile Driving Fatigue
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Evolving Gaussian Process Autoregression Based Learning of Human Motion Intent Using Improved Energy Kernel Method of EMG.

IEEE transactions on bio-medical engineering Jan 10, 2019
Continuous human motion intent learning may be modeled using a Gaussian process (GP) autoregression based evolving system to cope with the unspecified and time-varying motion patterns. Electromyography (EMG) signals are the primary input. GP is used ...
Algorithms Young Adult Adult Biomechanical Phenomena Male Humans Machine Learning Signal Processing, Computer-Assisted Exoskeleton Device Electromyography Intention Normal Distribution
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Improving the Quality of Synthetic FLAIR Images with Deep Learning Using a Conditional Generative Adversarial Network for Pixel-by-Pixel Image Translation.

AJNR. American journal of neuroradiology Jan 10, 2019
BACKGROUND AND PURPOSE: Synthetic FLAIR images are of lower quality than conventional FLAIR images. Here, we aimed to improve the synthetic FLAIR image quality using deep learning with pixel-by-pixel translation through conditional generative adversa...
Male Middle Aged Deep Learning Magnetic Resonance Imaging Image Interpretation, Computer-Assisted Artifacts Neuroimaging Humans Software Brain Female Adult
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Prediction of Recurrence after Transsphenoidal Surgery for Cushing's Disease: The Use of Machine Learning Algorithms.

Neuroendocrinology Jan 10, 2019
BACKGROUND: There are no reliable predictive models for recurrence after transsphenoidal surgery (TSS) for Cushing's disease (CD).
Young Adult Adult Male Models, Statistical Data Mining Algorithms Retrospective Studies Female Risk Factors Recurrence Pituitary ACTH Hypersecretion Humans Machine Learning
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Role of interleukin-3 as a prognostic marker in septic patients.

Revista Brasileira de terapia intensiva Jan 10, 2019
OBJECTIVE: To evaluate the accuracy of IL-3 to predict the outcome of septic patients.
Male Female Hospital Mortality Humans Middle Aged Reproducibility of Results Shock, Septic Prospective Studies Sepsis Aged Predictive Value of Tests Prognosis Cohort Studies Adult Intensive Care Units Interleukin-3 Sensitivity and Specificity
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Support vector machine-based multivariate pattern classification of methamphetamine dependence using arterial spin labeling.

Addiction biology Jan 9, 2019
Arterial spin labeling (ASL) magnetic resonance imaging has been widely applied to identify cerebral blood flow (CBF) abnormalities in a number of brain disorders. To evaluate its significance in detecting methamphetamine (MA) dependence, this study ...
Cerebrovascular Circulation Perfusion Imaging Spin Labels Male Humans Case-Control Studies Support Vector Machine Brain ROC Curve Magnetic Resonance Imaging Young Adult Imaging, Three-Dimensional Adult Area Under Curve Methamphetamine Amphetamine-Related Disorders
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Using Machine Learning to Identify Change in Surgical Decision Making in Current Use of Damage Control Laparotomy.

Journal of the American College of Surgeons Jan 9, 2019
BACKGROUND: In an earlier study, we reported the successful reduction in the use of damage control laparotomy (DCL); however, no change in the relative frequencies of specific indications was observed. In this study, we aimed to use machine learning ...
Clinical Decision-Making Female Young Adult Adult Sensitivity and Specificity Male Middle Aged Blood Transfusion Blood Pressure Trauma Severity Indices Humans Machine Learning Algorithms Patient Selection Retrospective Studies Quality Improvement Laparotomy Abdominal Injuries
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Qoala-T: A supervised-learning tool for quality control of FreeSurfer segmented MRI data.

NeuroImage Jan 8, 2019
Performing quality control to detect image artifacts and data-processing errors is crucial in structural magnetic resonance imaging, especially in developmental studies. Currently, many studies rely on visual inspection by trained raters for quality ...
Adult Datasets as Topic Sensitivity and Specificity Neuroimaging Humans Child Conduct Disorder Cross-Sectional Studies Autism Spectrum Disorder Human Development Adolescent Support Vector Machine Brain Longitudinal Studies Young Adult Magnetic Resonance Imaging Quality Control
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An EOG-based wheelchair robotic arm system for assisting patients with severe spinal cord injuries.

Journal of neural engineering Jan 8, 2019
OBJECTIVE: In this study, we combine a wheelchair and an intelligent robotic arm based on an electrooculogram (EOG) signal to help patients with spinal cord injuries (SCIs) accomplish a self-drinking task. The main challenge is to accurately control ...
Female Young Adult Adult Male Adolescent Humans Blinking Spinal Cord Injuries Man-Machine Systems Electrooculography Wheelchairs Eye Movements User-Computer Interface Robotics Psychomotor Performance
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