AIMC Topic: Support Vector Machine

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Comparing the analytical performances of Micro-NIR and FT-NIR spectrometers in the evaluation of acerola fruit quality, using PLS and SVM regression algorithms.

Talanta
The main goal of this study was to investigate the analytical performances of a state-of-the-art device, one of the smallest dispersion NIR spectrometers on the market (MicroNIR 1700), making a critical comparison with a benchtop FT-NIR spectrometer ...

A ternary classification using machine learning methods of distinct estrogen receptor activities within a large collection of environmental chemicals.

The Science of the total environment
Endocrine-disrupting chemicals (EDCs), which can threaten ecological safety and be harmful to human beings, have been cause for wide concern. There is a high demand for efficient methodologies for evaluating potential EDCs in the environment. Herein ...

A genotypic method for determining HIV-2 coreceptor usage enables epidemiological studies and clinical decision support.

Retrovirology
BACKGROUND: CCR5-coreceptor antagonists can be used for treating HIV-2 infected individuals. Before initiating treatment with coreceptor antagonists, viral coreceptor usage should be determined to ensure that the virus can use only the CCR5 corecepto...

Feature Fusion Based SVM Classifier for Protein Subcellular Localization Prediction.

Journal of integrative bioinformatics
For the importance of protein subcellular localization in different branches of life science and drug discovery, researchers have focused their attentions on protein subcellular localization prediction. Effective representation of features from prote...

A ℓ norm regularized multi-kernel learning for false positive reduction in Lung nodule CAD.

Computer methods and programs in biomedicine
OBJECTIVE: The aim of this paper is to describe a novel algorithm for False Positive Reduction in lung nodule Computer Aided Detection(CAD).

Semi-automated detection of anterior cruciate ligament injury from MRI.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: A radiologist's work in detecting various injuries or pathologies from radiological scans can be tiresome, time consuming and prone to errors. The field of computer-aided diagnosis aims to reduce these factors by introducin...

SnoReport 2.0: new features and a refined Support Vector Machine to improve snoRNA identification.

BMC bioinformatics
BACKGROUND: snoReport uses RNA secondary structure prediction combined with machine learning as the basis to identify the two main classes of small nucleolar RNAs, the box H/ACA snoRNAs and the box C/D snoRNAs. Here, we present snoReport 2.0, which s...

Using deep belief network modelling to characterize differences in brain morphometry in schizophrenia.

Scientific reports
Neuroimaging-based models contribute to increasing our understanding of schizophrenia pathophysiology and can reveal the underlying characteristics of this and other clinical conditions. However, the considerable variability in reported neuroimaging ...

Support vector machine classification trees based on fuzzy entropy of classification.

Analytica chimica acta
The support vector machine (SVM) is a powerful classifier that has recently been implemented in a classification tree (SVMTreeG). This classifier partitioned the data by finding gaps in the data space. For large and complex datasets, there may be no ...

Development of Type 2 Diabetes Mellitus Phenotyping Framework Using Expert Knowledge and Machine Learning Approach.

Journal of diabetes science and technology
BACKGROUND: Phenotyping is an automated technique that can be used to distinguish patients based on electronic health records. To improve the quality of medical care and advance type 2 diabetes mellitus (T2DM) research, the demand for T2DM phenotypin...