AIMC Topic: Support Vector Machine

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Indication of Electromagnetic Field Exposure via RBF-SVM Using Time-Series Features of Zebrafish Locomotion.

Sensors (Basel, Switzerland)
This paper introduces a novel model based on support vector machine with radial basis function kernel (RBF-SVM) using time-series features of zebrafish () locomotion exposed to different electromagnetic fields (EMFs) to indicate the corresponding EMF...

Machine learning for a combined electroencephalographic anesthesia index to detect awareness under anesthesia.

PloS one
Spontaneous electroencephalogram (EEG) and auditory evoked potentials (AEP) have been suggested to monitor the level of consciousness during anesthesia. As both signals reflect different neuronal pathways, a combination of parameters from both signal...

A Comparative Study of Supervised Machine Learning Algorithms for the Prediction of Long-Range Chromatin Interactions.

Genes
The role of three-dimensional genome organization as a critical regulator of gene expression has become increasingly clear over the last decade. Most of our understanding of this association comes from the study of long range chromatin interaction ma...

WiGAN: A WiFi Based Gesture Recognition System with GANs.

Sensors (Basel, Switzerland)
In recent years, a series of research experiments have been conducted on WiFi-based gesture recognition. However, current recognition systems are still facing the challenge of small samples and environmental dependence. To deal with the problem of pe...

Calculation of immune cell proportion from batch tumor gene expression profile based on support vector regression.

Journal of bioinformatics and computational biology
In addition to tumor cells, a large number of immune cells are found in the tumor microenvironment (TME) of cancer patients. Tumor-infiltrating immune cells play an important role in tumor progression and patient outcome. We improved the relative pro...

Machine learning models predicting multidrug resistant urinary tract infections using "DsaaS".

BMC bioinformatics
BACKGROUND: The scope of this work is to build a Machine Learning model able to predict patients risk to contract a multidrug resistant urinary tract infection (MDR UTI) after hospitalization. To achieve this goal, we used different popular Machine L...

CWLy-pred: A novel cell wall lytic enzyme identifier based on an improved MRMD feature selection method.

Genomics
Cell wall lytic enzymes play key roles in biochemical, morphological, genetic research and industry fields. To save time and labor costs, bioinformatic methods are usually adopted to narrow the scope of in vitro experimentation. In this paper, we est...

Leaf identification using radial basis function neural networks and SSA based support vector machine.

PloS one
In this research, an efficient scheme to identify leaf types is proposed. In that scheme, the leaf boundary points are fitted in a continuous contour using Radial Basis Function Neural Networks (RBFNN) to calculate the centroid of the leaf shape. Aft...

Disrupted rich-club network organization and individualized identification of patients with major depressive disorder.

Progress in neuro-psychopharmacology & biological psychiatry
BACKGROUND: Altered structural and functional brain networks have been extensively studied in major depressive disorder (MDD) patients. However, whether the differential connectivity patterns in the rich-club organization, assessed from structural br...