AIMC Topic: Support Vector Machine

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Improve the generalization of emotional classifiers across time by using training samples from different days.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Electroencephalographic (EEG)-based emotion recognition has attracted increasing attention from the field of human-computer interaction (HCI). However, there are a number of challenges for machines to correctly recognize human emotional states. One p...

Detection of steering direction using EEG recordings based on sample entropy and time-frequency analysis.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Monitoring driver's intentions beforehand is an ambitious aim, which will bring a huge impact on the society by preventing traffic accidents. Hence, in this preliminary study we recorded high resolution electroencephalography (EEG) from 5 subjects wh...

Encoding physiological signals as images for affective state recognition using convolutional neural networks.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Affective state recognition based on multiple modalities of physiological signals has been a hot research topic. Traditional methods require designing hand-crafted features based on domain knowledge, which is time-consuming and has not achieved a sat...

Support vectors machine classification of surface electromyography for non-invasive naturally controlled hand prostheses.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
The scientific researches in human rehabilitation techniques have continually evolved to offer again the mobility and freedom lost to disability. Many systems managed by myoelectric signals intended to mimic the movement of the human arm still have r...

Forecasting nanoparticle toxicity using nonlinear predictive regressor learning systems.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Nanoparticle (NP) toxicity is determined by a vast number of topological, sterical, physico-chemical as well as biological properties, rendering a priori evaluation of the effect of NP on biological tissue as arduous as it is necessary and urgent. We...

MSLVP: prediction of multiple subcellular localization of viral proteins using a support vector machine.

Molecular bioSystems
Knowledge of the subcellular location (SCL) of viral proteins in the host cell is important for understanding their function in depth. Therefore, we have developed "MSLVP", a two-tier prediction algorithm for predicting multiple SCLs of viral protein...

Sieve-based coreference resolution enhances semi-supervised learning model for chemical-induced disease relation extraction.

Database : the journal of biological databases and curation
The BioCreative V chemical-disease relation (CDR) track was proposed to accelerate the progress of text mining in facilitating integrative understanding of chemicals, diseases and their relations. In this article, we describe an extension of our syst...

Discriminative analysis of schizophrenia using support vector machine and recursive feature elimination on structural MRI images.

Medicine
Structural abnormalities in schizophrenia (SZ) patients have been well documented with structural magnetic resonance imaging (MRI) data using voxel-based morphometry (VBM) and region of interest (ROI) analyses. However, these analyses can only detect...

Classifying Schizophrenia Using Multimodal Multivariate Pattern Recognition Analysis: Evaluating the Impact of Individual Clinical Profiles on the Neurodiagnostic Performance.

Schizophrenia bulletin
Previous studies have shown that structural brain changes are among the best-studied candidate markers for schizophrenia (SZ) along with functional connectivity (FC) alterations of resting-state (RS) patterns. This study aimed to investigate effects ...

Comparison of Feature Selection Techniques in Machine Learning for Anatomical Brain MRI in Dementia.

Neuroinformatics
We present a comparative split-half resampling analysis of various data driven feature selection and classification methods for the whole brain voxel-based classification analysis of anatomical magnetic resonance images. We compared support vector ma...