AIMC Topic: Support Vector Machine

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Detection of lung cancer in exhaled breath with an electronic nose using support vector machine analysis.

Journal of breath research
Lung cancer is one of the most common malignancies and has a low 5-year survival rate. There are no cheap, simple and widely available screening methods for the early diagnostics of lung cancer. The aim of this study was to determine whether analysis...

An Ameliorated Prediction of Drug-Target Interactions Based on Multi-Scale Discrete Wavelet Transform and Network Features.

International journal of molecular sciences
The prediction of drug-target interactions (DTIs) via computational technology plays a crucial role in reducing the experimental cost. A variety of state-of-the-art methods have been proposed to improve the accuracy of DTI predictions. In this paper,...

Ambient Air Quality Classification by Grey Wolf Optimizer Based Support Vector Machine.

Journal of environmental and public health
With the development of society along with an escalating population, the concerns regarding public health have cropped up. The quality of air becomes primary concern regarding constant increase in the number of vehicles and industrial development. Wi...

Enhancement of hepatitis virus immunoassay outcome predictions in imbalanced routine pathology data by data balancing and feature selection before the application of support vector machines.

BMC medical informatics and decision making
BACKGROUND: Data mining techniques such as support vector machines (SVMs) have been successfully used to predict outcomes for complex problems, including for human health. Much health data is imbalanced, with many more controls than positive cases.

"What is relevant in a text document?": An interpretable machine learning approach.

PloS one
Text documents can be described by a number of abstract concepts such as semantic category, writing style, or sentiment. Machine learning (ML) models have been trained to automatically map documents to these abstract concepts, allowing to annotate ve...

Prediction of N-linked glycosylation sites using position relative features and statistical moments.

PloS one
Glycosylation is one of the most complex post translation modification in eukaryotic cells. Almost 50% of the human proteome is glycosylated as glycosylation plays a vital role in various biological functions such as antigen's recognition, cell-cell ...

An Alzheimers disease related genes identification method based on multiple classifier integration.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Alzheimers disease (AD) is a fatal neurodegenerative disease and the onset of AD is insidious. Full understanding of the AD-related genes (ADGs) has not been completed. The National Center for Biotechnology Information (NCBI...

Performance comparison between wrist and chest actigraphy in combination with heart rate variability for sleep classification.

Computers in biology and medicine
The concurrent usage of actigraphy and heart rate variability (HRV) for sleep efficiency quantification is still matter of investigation. This study compared chest (CACT) and wrist (WACT) actigraphy (actigraphs positioned on chest and wrist, respecti...

Shallow Representation Learning via Kernel PCA Improves QSAR Modelability.

Journal of chemical information and modeling
Linear models offer a robust, flexible, and computationally efficient set of tools for modeling quantitative structure-activity relationships (QSARs) but have been eclipsed in performance by nonlinear methods. Support vector machines (SVMs) and neura...

A nonparametric Bayesian method of translating machine learning scores to probabilities in clinical decision support.

BMC bioinformatics
BACKGROUND: Probabilistic assessments of clinical care are essential for quality care. Yet, machine learning, which supports this care process has been limited to categorical results. To maximize its usefulness, it is important to find novel approach...