AIMC Topic: Linear Models

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Extreme learning machines: a new approach for modeling dissolved oxygen (DO) concentration with and without water quality variables as predictors.

Environmental science and pollution research international May 30, 2017
In this paper, several extreme learning machine (ELM) models, including standard extreme learning machine with sigmoid activation function (S-ELM), extreme learning machine with radial basis activation function (R-ELM), online sequential extreme lear...
Rivers Linear Models Neural Networks, Computer Oxygen Water Quality
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QSAR studies of the bioactivity of hepatitis C virus (HCV) NS3/4A protease inhibitors by multiple linear regression (MLR) and support vector machine (SVM).

Bioorganic & medicinal chemistry letters May 3, 2017
In this study, quantitative structure-activity relationship (QSAR) models using various descriptor sets and training/test set selection methods were explored to predict the bioactivity of hepatitis C virus (HCV) NS3/4A protease inhibitors by using a ...
Antiviral Agents Support Vector Machine Serine Proteases Dose-Response Relationship, Drug Molecular Structure Quantitative Structure-Activity Relationship Hepacivirus Viral Nonstructural Proteins Linear Models Protease Inhibitors
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Remote sensing-based measurement of Living Environment Deprivation: Improving classical approaches with machine learning.

PloS one May 2, 2017
This paper provides evidence on the usefulness of very high spatial resolution (VHR) imagery in gathering socioeconomic information in urban settlements. We use land cover, spectral, structure and texture features extracted from a Google Earth image ...
Cities Humans Socioeconomic Factors Urban Population Machine Learning Data Interpretation, Statistical England Remote Sensing Technology Least-Squares Analysis Linear Models
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A Novel Continuous Blood Pressure Estimation Approach Based on Data Mining Techniques.

IEEE journal of biomedical and health informatics Apr 28, 2017
Continuous blood pressure (BP) estimation using pulse transit time (PTT) is a promising method for unobtrusive BP measurement. However, the accuracy of this approach must be improved for it to be viable for a wide range of applications. This study pr...
Humans Female Photoplethysmography Electrocardiography Blood Pressure Determination Support Vector Machine Young Adult Adult Male Linear Models Blood Pressure Signal Processing, Computer-Assisted Data Mining
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Spatiotemporal signal classification via principal components of reservoir states.

Neural networks : the official journal of the International Neural Network Society Apr 24, 2017
Reservoir computing is a recently introduced machine learning paradigm that has been shown to be well-suited for the processing of spatiotemporal data. Rather than training the network node connections and weights via backpropagation in traditional r...
Principal Component Analysis Linear Models Neural Networks, Computer
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New model for prediction binary mixture of antihistamine decongestant using artificial neural networks and least squares support vector machine by spectrophotometry method.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy Apr 5, 2017
In the present study, artificial neural networks (ANNs) and least squares support vector machines (LS-SVM) as intelligent methods based on absorption spectra in the range of 230-300nm have been used for determination of antihistamine decongestant con...
Sensitivity and Specificity Support Vector Machine Neural Networks, Computer Least-Squares Analysis Linear Models Algorithms Reproducibility of Results Spectrophotometry Histamine Antagonists Nasal Decongestants
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Utilization of machine learning for prediction of post-traumatic stress: a re-examination of cortisol in the prediction and pathways to non-remitting PTSD.

Translational psychiatry Mar 21, 2017
To date, studies of biological risk factors have revealed inconsistent relationships with subsequent post-traumatic stress disorder (PTSD). The inconsistent signal may reflect the use of data analytic tools that are ill equipped for modeling the comp...
Psychological Trauma Receptors, Glucocorticoid Saliva Lymphocytes Heart Rate Adrenocorticotropic Hormone Linear Models Urine Wounds and Injuries Area Under Curve Emergency Service, Hospital Norepinephrine Hydrocortisone Support Vector Machine Longitudinal Studies Blood Pressure Female Young Adult Male Adult Humans Risk Assessment Machine Learning Stress Disorders, Post-Traumatic Algorithms ROC Curve
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Ontogenetic Shifts in Brain Organization in the Bluespotted Stingray Neotrygon kuhlii (Chondrichthyes: Dasyatidae).

Brain, behavior and evolution Feb 28, 2017
Fishes exhibit lifelong neurogenesis and continual brain growth. One consequence of this continual growth is that the nervous system has the potential to respond with enhanced plasticity to changes in ecological conditions that occur during ontogeny....
Computer Graphics Skates, Fish Linear Models Biological Ontologies Species Specificity Brain Female Animals Male
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A mathematical model for the two-learners problem.

Journal of neural engineering Feb 22, 2017
OBJECTIVE: We present the first generic theoretical formulation of the co-adaptive learning problem and give a simple example of two interacting linear learning systems, a human and a machine.
Humans Machine Learning Computer Simulation Learning Animals Game Theory Models, Neurological Linear Models Man-Machine Systems
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Subject-based discriminative sparse representation model for detection of concealed information.

Computer methods and programs in biomedicine Feb 20, 2017
BACKGROUND AND OBJECTIVES: The use of machine learning approaches in concealed information test (CIT) plays a key role in the progress of this neurophysiological field. In this paper, we presented a new machine learning method for CIT in which each s...
Humans Truth Disclosure Artificial Intelligence Reproducibility of Results Machine Learning Guilt Linear Models Sensitivity and Specificity Algorithms Random Allocation Support Vector Machine Electroencephalography Learning Signal-To-Noise Ratio Brain Mapping Electrodes Crime Healthy Volunteers
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