AIMC Topic: Support Vector Machine

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gDNA-Prot: Predict DNA-binding proteins by employing support vector machine and a novel numerical characterization of protein sequence.

Journal of theoretical biology
DNA-binding proteins are the functional proteins in cells, which play an important role in various essential biological activities. An effective and fast computational method gDNA-Prot is proposed to predict DNA-binding proteins in this paper, which ...

eRFSVM: a hybrid classifier to predict enhancers-integrating random forests with support vector machines.

Hereditas
BACKGROUND: Enhancers are tissue specific distal regulation elements, playing vital roles in gene regulation and expression. The prediction and identification of enhancers are important but challenging issues for bioinformatics studies. Existing comp...

SVM-Based System for Prediction of Epileptic Seizures From iEEG Signal.

IEEE transactions on bio-medical engineering
OBJECTIVE: This paper describes a data-analytic modeling approach for the prediction of epileptic seizures from intracranial electroencephalogram (iEEG) recording of brain activity. Even though it is widely accepted that statistical characteristics o...

Analyzing the performance of fluorescence parameters in the monitoring of leaf nitrogen content of paddy rice.

Scientific reports
Leaf nitrogen content (LNC) is a significant factor which can be utilized to monitor the status of paddy rice and it requires a reliable approach for fast and precise quantification. This investigation aims to quantitatively analyze the correlation b...

A support vector machine-based method to identify mild cognitive impairment with multi-level characteristics of magnetic resonance imaging.

Neuroscience
Mild cognitive impairment (MCI) represents a transitional state between normal aging and Alzheimer's disease (AD). Non-invasive diagnostic methods are desirable to identify MCI for early therapeutic interventions. In this study, we proposed a support...

Using machine learning to support healthcare professionals in making preauthorisation decisions.

International journal of medical informatics
BACKGROUND: Preauthorisation is a control mechanism that is used by Health Insurance Providers (HIPs) to minimise wastage of resources through the denial of the procedures that were unduly requested. However, an efficient preauthorisation process req...

Computational neuroanatomy using brain deformations: From brain parcellation to multivariate pattern analysis and machine learning.

Medical image analysis
The past 20 years have seen a mushrooming growth of the field of computational neuroanatomy. Much of this work has been enabled by the development and refinement of powerful, high-dimensional image warping methods, which have enabled detailed brain p...

Ensemble Feature Learning of Genomic Data Using Support Vector Machine.

PloS one
The identification of a subset of genes having the ability to capture the necessary information to distinguish classes of patients is crucial in bioinformatics applications. Ensemble and bagging methods have been shown to work effectively in the proc...

A machine-learning approach for predicting palmitoylation sites from integrated sequence-based features.

Journal of bioinformatics and computational biology
Palmitoylation is the covalent attachment of lipids to amino acid residues in proteins. As an important form of protein posttranslational modification, it increases the hydrophobicity of proteins, which contributes to the protein transportation, orga...

Lung Cancer Detection Using Fuzzy Auto-Seed Cluster Means Morphological Segmentation and SVM Classifier.

Journal of medical systems
An effective fuzzy auto-seed cluster means morphological algorithm developed in this work to segment the lung nodules from the consecutive slices of Computer Tomography (CT) images to detect the lung cancer. The initial cluster values were chosen aut...