AIMC Topic: Support Vector Machine

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Diagnosis of the Severity of Fusarium Head Blight of Wheat Ears on the Basis of Image and Spectral Feature Fusion.

Sensors (Basel, Switzerland) May 20, 2020
head blight (FHB), one of the most prevalent and damaging infection diseases of wheat, affects quality and safety of associated food. In this study, to realize the early accurate monitoring of FHB, a diagnostic model of disease severity was proposed...
Support Vector Machine Triticum Fusarium Plant Diseases Algorithms
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Automated detection of the head-twitch response using wavelet scalograms and a deep convolutional neural network.

Scientific reports May 20, 2020
Hallucinogens induce the head-twitch response (HTR), a rapid reciprocal head movement, in mice. Although head twitches are usually identified by direct observation, they can also be assessed using a head-mounted magnet and a magnetometer. Procedures ...
Support Vector Machine Head Movements Drug Evaluation, Preclinical Behavior Observation Techniques Animals Hallucinogens Magnetometry Male Reproducibility of Results Models, Animal Mice Sensitivity and Specificity Magnets Behavior, Animal
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In Silico Prediction of Intestinal Permeability by Hierarchical Support Vector Regression.

International journal of molecular sciences May 19, 2020
The vast majority of marketed drugs are orally administrated. As such, drug absorption is one of the important drug metabolism and pharmacokinetics parameters that should be assessed in the process of drug discovery and development. A nonlinear quant...
Humans Computer Simulation Permeability Rats Reproducibility of Results Support Vector Machine Animals Regression Analysis Intestines
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Uncovering the prognostic gene signatures for the improvement of risk stratification in cancers by using deep learning algorithm coupled with wavelet transform.

BMC bioinformatics May 19, 2020
BACKGROUND: The aim of gene expression-based clinical modelling in tumorigenesis is not only to accurately predict the clinical endpoints, but also to reveal the genome characteristics for downstream analysis for the purpose of understanding the mech...
Gene Expression Proportional Hazards Models Wavelet Analysis Humans Deep Learning Support Vector Machine Algorithms Prognosis Risk Assessment Neoplasms
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Enhancing SVM for survival data using local invariances and weighting.

BMC bioinformatics May 19, 2020
BACKGROUND: The necessity to analyze medium-throughput data in epidemiological studies with small sample size, particularly when studying biomedical data may hinder the use of classical statistical methods. Support vector machines (SVM) models can be...
Humans Support Vector Machine Survival Analysis Proportional Hazards Models
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Learning soft sensors using time difference-based multi-kernel relevance vector machine with applications for quality-relevant monitoring in wastewater treatment.

Environmental science and pollution research international May 18, 2020
Considering the time-varying, uncertain and non-linear properties of the wastewater treatment process (WWTPs), a novel multi-kernel relevance vector machine (MRVM) soft sensor based on time difference (TD) is proposed to predict the quality-relevant ...
Algorithms Support Vector Machine Artificial Intelligence Wastewater
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Interpretable Learning Approaches in Resting-State Functional Connectivity Analysis: The Case of Autism Spectrum Disorder.

Computational and mathematical methods in medicine May 18, 2020
Deep neural networks have recently been applied to the study of brain disorders such as autism spectrum disorder (ASD) with great success. However, the internal logics of these networks are difficult to interpret, especially with regard to how specif...
Neural Networks, Computer Linear Models Databases, Factual Computational Biology Autism Spectrum Disorder Case-Control Studies Humans Connectome Support Vector Machine Deep Learning Magnetic Resonance Imaging Functional Neuroimaging
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EEG Signal and Feature Interaction Modeling-Based Eye Behavior Prediction Research.

Computational and mathematical methods in medicine May 16, 2020
In recent years, with the development of brain science and biomedical engineering, as well as the rapid development of electroencephalogram (EEG) signal analysis methods, using EEG signals to monitor human health has become a very popular research fi...
Head Movements Support Vector Machine Algorithms Humans Ocular Physiological Phenomena Electroencephalography Computational Biology Neural Networks, Computer Wavelet Analysis Signal Processing, Computer-Assisted Logistic Models Brain Waves Fatigue
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Machine learning algorithms for predicting malnutrition among under-five children in Bangladesh.

Nutrition (Burbank, Los Angeles County, Calif.) May 15, 2020
OBJECTIVE: The aim of this study was is to predict malnutrition status in under-five children in Bangladesh by using various machine learning (ML) algorithms.
Child Support Vector Machine Malnutrition Humans Bangladesh Machine Learning Algorithms
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Machine Learning (ML) based-method applied in recurrent pregnancy loss (RPL) patients diagnostic work-up: a potential innovation in common clinical practice.

Scientific reports May 14, 2020
RPL is a very debated condition, in which many issues concerning definition, etiological factors to investigate or therapies to apply are still controversial. ML could help clinicians to reach an objectiveness in RPL classification and access to care...
Machine Learning Algorithms Biomarkers Humans Young Adult Adult Middle Aged Clinical Decision-Making Pregnancy Female Disease Management Abortion, Habitual Adolescent Support Vector Machine
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