Humans

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Predicting Organ Toxicity Using in Vitro Bioactivity Data and Chemical Structure.

Chemical research in toxicology Oct 9, 2017
Animal testing alone cannot practically evaluate the health hazard posed by tens of thousands of environmental chemicals. Computational approaches making use of high-throughput experimental data may provide more efficient means to predict chemical to...
Environmental Pollutants Models, Biological Quantitative Structure-Activity Relationship Toxicity Tests Humans Machine Learning Databases, Factual Animals
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Exposome-Scale Investigations Guided by Global Metabolomics, Pathway Analysis, and Cognitive Computing.

Analytical chemistry Oct 9, 2017
Concurrent exposure to a wide variety of xenobiotics and their combined toxic effects can play a pivotal role in health and disease, yet are largely unexplored. Investigating the totality of these exposures, i.e., the "exposome", and their specific b...
Male Genomics Databases, Genetic Metabolomics Humans Artificial Intelligence
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On neuromechanical approaches for the study of biological and robotic grasp and manipulation.

Journal of neuroengineering and rehabilitation Oct 9, 2017
Biological and robotic grasp and manipulation are undeniably similar at the level of mechanical task performance. However, their underlying fundamental biological vs. engineering mechanisms are, by definition, dramatically different and can even be a...
Humans Biomechanical Phenomena Hand Strength Robotics
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Multiobjective differential evolution-based multifactor dimensionality reduction for detecting gene-gene interactions.

Scientific reports Oct 9, 2017
Epistasis within disease-related genes (gene-gene interactions) was determined through contingency table measures based on multifactor dimensionality reduction (MDR) using single-nucleotide polymorphisms (SNPs). Most MDR-based methods use the single ...
Epistasis, Genetic Multifactor Dimensionality Reduction Coronary Artery Disease Genetic Loci Gene Frequency Humans Computer Simulation Polymorphism, Single Nucleotide Models, Genetic
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Development of A Machine Learning Algorithm to Classify Drugs Of Unknown Fetal Effect.

Scientific reports Oct 9, 2017
Many drugs commonly prescribed during pregnancy lack a fetal safety recommendation - called FDA 'category C' drugs. This study aims to classify these drugs into harmful and safe categories using knowledge gained from chemoinformatics (i.e., pharmacol...
(1)
Embryo Loss United States Food and Drug Administration Databases as Topic Fetus Algorithms Female Adult Infant United States Models, Theoretical Drug-Related Side Effects and Adverse Reactions Humans Machine Learning
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A brain-computer interface based on functional transcranial doppler ultrasound using wavelet transform and support vector machines.

Journal of neuroscience methods Oct 7, 2017
BACKGROUND: Functional transcranial Doppler (fTCD) is an ultrasound based neuroimaging technique used to assess neural activation that occurs during a cognitive task through measuring velocity of cerebral blood flow.
Imagination Ultrasonography, Doppler, Transcranial Neuropsychological Tests Cerebrovascular Circulation Space Perception Young Adult Male Functional Neuroimaging Humans Cognition Rest Support Vector Machine Brain Feasibility Studies Brain-Computer Interfaces Language Wavelet Analysis Rotation Female Blood Flow Velocity Linear Models
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A hierarchical structure for human behavior classification using STN local field potentials.

Journal of neuroscience methods Oct 7, 2017
BACKGROUND: Classification of human behavior from brain signals has potential application in developing closed-loop deep brain stimulation (DBS) systems. This paper presents a human behavior classification using local field potential (LFP) signals re...
Aged Male Middle Aged Speech Support Vector Machine Parkinson Disease Mouth Humans Female Motor Activity Upper Extremity Deep Brain Stimulation Cortical Synchronization Wavelet Analysis Subthalamic Nucleus Multilevel Analysis
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Supervised machine learning techniques to predict binding affinity. A study for cyclin-dependent kinase 2.

Biochemical and biophysical research communications Oct 7, 2017
Here we report the development of a machine-learning model to predict binding affinity based on the crystallographic structures of protein-ligand complexes. We used an ensemble of crystallographic structures (resolution better than 1.5 Å resolution) ...
(1)
Ligands Inhibitory Concentration 50 Datasets as Topic Protein Kinase Inhibitors Thermodynamics Cyclin-Dependent Kinase 2 Humans Molecular Docking Simulation Antineoplastic Agents Drug Design ROC Curve Databases, Protein Supervised Machine Learning
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Improving the Accuracy and Training Speed of Motor Imagery Brain-Computer Interfaces Using Wavelet-Based Combined Feature Vectors and Gaussian Mixture Model-Supervectors.

Sensors (Basel, Switzerland) Oct 7, 2017
In this paper, we propose a set of wavelet-based combined feature vectors and a Gaussian mixture model (GMM)-supervector to enhance training speed and classification accuracy in motor imagery brain-computer interfaces. The proposed method is configur...
Algorithms Support Vector Machine Normal Distribution Electroencephalography Models, Biological Brain-Computer Interfaces Humans Wavelet Analysis Neurology
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Learning ensemble classifiers for diabetic retinopathy assessment.

Artificial intelligence in medicine Oct 6, 2017
Diabetic retinopathy is one of the most common comorbidities of diabetes. Unfortunately, the recommended annual screening of the eye fundus of diabetic patients is too resource-consuming. Therefore, it is necessary to develop tools that may help doct...
Humans Diabetic Retinopathy Machine Learning Reproducibility of Results Risk Factors Risk Assessment Time Factors Decision Support Techniques Prognosis Electronic Health Records Clinical Decision-Making Fuzzy Logic Decision Trees Decision Support Systems, Clinical Predictive Value of Tests Diabetes Mellitus, Type 2 Diabetes Mellitus, Type 1
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