AIMC Topic: Support Vector Machine

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Leveraging machine learning to distinguish between bacterial and viral induced pharyngitis using hematological markers: a retrospective cohort study.

Scientific reports
Accurate differentiation between bacterial and viral-induced pharyngitis is recognized as essential for personalized treatment and judicious antibiotic use. From a cohort of 693 patients with pharyngitis, data from 197 individuals clearly diagnosed w...

Distinctive approach in brain tumor detection and feature extraction using biologically inspired DWT method and SVM.

Scientific reports
Brain tumors result from uncontrolled cell growth, potentially leading to fatal consequences if left untreated. While significant efforts have been made with some promising results, the segmentation and classification of brain tumors remain challengi...

Optimizing the selection of natural fibre reinforcement and polymer matrix for plastic composite using LS-SVM technique.

Chemosphere
The manufacturing sector is paying close attention to plastic matrix composites (PMCs) reinforced with natural fibres for improving their products. Due to the fact that PMC reinforced with naturally occurring fibres is more affordable and has superio...

Cross-subject emotion recognition using hierarchical feature optimization and support vector machine with multi-kernel collaboration.

Physiological measurement
. Due to individual differences, it is greatly challenging to realize the multiple types of emotion identification across subjects.. In this research, a hierarchical feature optimization method is proposed in order to represent emotional states effec...

An Online Support Vector Machine Algorithm for Dynamic Social Network Monitoring.

Neural networks : the official journal of the International Neural Network Society
Online monitoring of social networks offers exciting features for platforms, enabling both technical and behavioral analysis. Numerous studies have explored the adaptation of traditional quality control methods for detecting change points within soci...

Toxicity prediction of nanoparticles using machine learning approaches.

Toxicology
Nanoparticle toxicity analysis is critical for evaluating the safety of nanomaterials due to their potential harm to the biological system. However, traditional experimental methods for evaluating nanoparticle toxicity are expensive and time-consumin...

Population-Based Artificial Intelligence Assessment of Relationship Between the Risk Factors for Diabetic Retinopathy in Indian Population.

Ophthalmic epidemiology
PURPOSE: Risk factors (RFs), like 'body mass index (BMI),' 'age,' and 'gender' correlate with Diabetic Retinopathy (DR) diagnosis and have been widely studied. This study examines how these three secondary RFs independently affect the predictive capa...

Prediction model of subacromial pain syndrome in assembly workers using shoulder range of motion and muscle strength based on support vector machine.

Ergonomics
Subacromial pain syndrome (SAPS) is the most common upper-extremity musculoskeletal problem among workers. In this study, a machine learning model was built to predict and classify the presence or absence of SAPS in assembly workers with shoulder joi...

Variable Projection Support Vector Machines and Some Applications Using Adaptive Hermite Expansions.

International journal of neural systems
In this paper, we develop the so-called variable projection support vector machine (VP-SVM) algorithm that is a generalization of the classical SVM. In fact, the VP block serves as an automatic feature extractor to the SVM, which are trained simultan...

Evaluating Machine Learning Methods of Analyzing Multiclass Metabolomics.

Journal of chemical information and modeling
Multiclass metabolomic studies have become popular for revealing the differences in multiple stages of complex diseases, various lifestyles, or the effects of specific treatments. In multiclass metabolomics, there are multiple data manipulation steps...