AIMC Topic: Support Vector Machine

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Fusing H NMR and Raman experimental data for the improvement of wine recognition models.

Food chemistry
The present study proposes the development of new wine recognition models based on Artificial Intelligence (AI) applied to the mid-level data fusion of H NMR and Raman data. In this regard, a supervised machine learning method, namely Support Vector ...

Optimization of mid-infrared noninvasive blood-glucose prediction model by support vector regression coupled with different spectral features.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Mid-infrared spectral analysis of glucose in subcutaneous interstitial fluid has been widely employed as a noninvasive alternative to the standard blood-glucose detection requiring blood-sampling via skin-puncturing, but improving the confidence leve...

Feature evaluation for myoelectric pattern recognition of multiple nearby reaching targets.

Medical engineering & physics
Intention detection of the reaching movement is considerable for myoelectric human and machine collaboration applications. A comprehensive set of handcrafted features was mined from windows of electromyogram (EMG) of the upper-limb muscles while reac...

Enhancing microalgae classification accuracy in marine ecosystems through convolutional neural networks and support vector machines.

Marine pollution bulletin
Accurately classifying microalgae species is vital for monitoring marine ecosystems and managing the emergence of marine mucilage, which is crucial for monitoring mucilage phenomena in marine environments. Traditional methods have been inadequate due...

A Support Vector Machine-Assisted Metabolomics Approach for Non-Targeted Screening of Multi-Class Pesticides and Veterinary Drugs in Maize.

Molecules (Basel, Switzerland)
The contamination risks of plant-derived foods due to the co-existence of pesticides and veterinary drugs (P&VDs) have not been fully understood. With an increasing number of unexpected P&VDs illegally added to foods, it is essential to develop a non...

Identifying significant structural factors associated with knee pain severity in patients with osteoarthritis using machine learning.

Scientific reports
Our main objective was to use machine learning methods to identify significant structural factors associated with pain severity in knee osteoarthritis patients. Additionally, we assessed the potential of various classes of imaging data using machine ...

A novel bounded loss framework for support vector machines.

Neural networks : the official journal of the International Neural Network Society
This paper introduces a novel bounded loss framework for SVM and SVR. Specifically, using the Pinball loss as an illustration, we devise a novel bounded exponential quantile loss (L-loss) for both support vector machine classification and regression ...

Assessing the impact of climate variability on maize yields in the different regions of Ghana-A machine learning perspective.

PloS one
Climate variability has become one of the most pressing issues of our time, affecting various aspects of the environment, including the agriculture sector. This study examines the impact of climate variability on Ghana's maize yield for all agro-ecol...

EMG-based prediction of step direction for a better control of lower limb wearable devices.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: Lower-limb wearable devices can significantly improve the quality of life of subjects suffering from debilitating conditions, such as amputations, neurodegenerative disorders, and stroke-related impairments. Current control...

Learning and depicting lobe-based radiomics feature for COPD Severity staging in low-dose CT images.

BMC pulmonary medicine
BACKGROUND: Chronic obstructive pulmonary disease (COPD) is a prevalent and debilitating respiratory condition that imposes a significant healthcare burden worldwide. Accurate staging of COPD severity is crucial for patient management and treatment p...