AIMC Topic: Humans

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The convergence of artificial intelligence and chemistry for improved drug discovery.

Future medicinal chemistry Nov 30, 2018
Pharmaceutical Preparations Chemistry Techniques, Synthetic Computer-Aided Design Drug Design Drug Discovery Humans Artificial Intelligence
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A comparison of logistic regression models with alternative machine learning methods to predict the risk of in-hospital mortality in emergency medical admissions via external validation.

Health informatics journal Nov 29, 2018
We compare the performance of logistic regression with several alternative machine learning methods to estimate the risk of death for patients following an emergency admission to hospital based on the patients' first blood test results and physiologi...
Logistic Models Emergency Service, Hospital Patient Admission Hospitalization Hospital Mortality ROC Curve Humans Machine Learning
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3D Auto-Context-Based Locality Adaptive Multi-Modality GANs for PET Synthesis.

IEEE transactions on medical imaging Nov 29, 2018
Positron emission tomography (PET) has been substantially used recently. To minimize the potential health risk caused by the tracer radiation inherent to PET scans, it is of great interest to synthesize the high-quality PET image from the low-dose on...
Magnetic Resonance Imaging Brain Humans Deep Learning Phantoms, Imaging Positron-Emission Tomography Databases, Factual Imaging, Three-Dimensional Radiation Dosage
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Toward a motor signature in autism: Studies from human-machine interaction.

L'Encephale Nov 29, 2018
BACKGROUND: Autism spectrum disorder (ASD) is a heterogeneous group of neurodevelopmental disorders which core symptoms are impairments in socio-communication and repetitive symptoms and stereotypies. Although not cardinal symptoms per se, motor impa...
Male Diagnosis, Computer-Assisted Motor Skills Disorders Child Autism Spectrum Disorder Diagnostic Techniques, Neurological Humans Posture Computer Simulation Machine Learning Robotics Female Motor Activity
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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...
Middle Aged Deep Learning Image Processing, Computer-Assisted Magnetic Resonance Imaging Humans Datasets as Topic Neuroimaging Neuroanatomy Neural Networks, Computer Aged, 80 and over Brain Young Adult Aged Adult
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Effects of a cyborg-type robot suit HAL on cardiopulmonary burden during exercise in normal subjects.

European journal of applied physiology Nov 29, 2018
BACKGROUND: The hybrid assistive limb (HAL) is the world's first cyborg-type robot suit that provides motion assistance to physically challenged patients. HAL is expected to expand the possibilities of exercise therapy for severe cardiac patients who...
Exoskeleton Device Oxygen Consumption Exercise Test Exercise Tolerance Exercise Robotics Humans Adult Male Middle Aged
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Machine learning studies on major brain diseases: 5-year trends of 2014-2018.

Japanese journal of radiology Nov 29, 2018
In the recent 5 years (2014-2018), there has been growing interest in the use of machine learning (ML) techniques to explore image diagnosis and prognosis of therapeutic lesion changes within the area of neuroradiology. However, to date, the majority...
Humans Machine Learning Brain Brain Diseases Neuroimaging
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Improvement of image quality at CT and MRI using deep learning.

Japanese journal of radiology Nov 29, 2018
Deep learning has been developed by computer scientists. Here, we discuss techniques for improving the image quality of diagnostic computed tomography and magnetic resonance imaging with the aid of deep learning. We categorize the techniques for impr...
Deep Learning Image Processing, Computer-Assisted Magnetic Resonance Imaging Humans Algorithms Tomography, X-Ray Computed Artifacts
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Automated ASPECTS on Noncontrast CT Scans in Patients with Acute Ischemic Stroke Using Machine Learning.

AJNR. American journal of neuroradiology Nov 29, 2018
BACKGROUND AND PURPOSE: Alberta Stroke Program Early CT Score (ASPECTS) was devised as a systematic method to assess the extent of early ischemic change on noncontrast CT (NCCT) in patients with acute ischemic stroke (AIS). Our aim was to automate AS...
Tomography, X-Ray Computed Female Aged Humans Machine Learning Image Interpretation, Computer-Assisted Neuroimaging Alberta Diffusion Magnetic Resonance Imaging Middle Aged Stroke Brain Ischemia Aged, 80 and over Sensitivity and Specificity Male
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Advances with support vector machines for novel drug discovery.

Expert opinion on drug discovery Nov 29, 2018
Novel drug discovery remains an enormous challenge, with various computer-aided drug design (CADD) approaches having been widely employed for this purpose. CADD, specifically the commonly used support vector machines (SVMs), can employ machine learni...
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Humans Drug Discovery Machine Learning Support Vector Machine Drug Design Quantitative Structure-Activity Relationship
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