AIMC Topic: Support Vector Machine

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VOC data-driven evaluation of vehicle cabin odor: from ANN to CNN-BiLSTM.

Environmental science and pollution research international
Emissions of volatile organic compounds (VOCs) in vehicles represent a significant problem, causing unpleasant odors. To mitigate VOCs and odors in vehicles, it is critical to choose interior parts with low odor and VOC emissions. However, prevailing...

Risk adjusted EWMA control chart based on support vector machine with application to cardiac surgery data.

Scientific reports
In the current study, we demonstrate the use of a quality framework to review the process for improving the quality and safety of the patient in the health care department. The researchers paid attention to assessing the performance of the health car...

Development of new materials for electrothermal metals using data driven and machine learning.

PloS one
After adopting a combined approach of data-driven methods and machine learning, the prediction of material performance and the optimization of composition design can significantly reduce the development time of materials at a lower cost. In this rese...

Application of machine learning algorithms to identify people with low bone density.

Frontiers in public health
BACKGROUND: Osteoporosis is becoming more common worldwide, imposing a substantial burden on individuals and society. The onset of osteoporosis is subtle, early detection is challenging, and population-wide screening is infeasible. Thus, there is a n...

Comparing visible and near infrared 'point' spectroscopy and hyperspectral imaging techniques to visualize the variability of apple firmness.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
In this work, visible and near-infrared 'point' (Vis-NIR) spectroscopy and hyperspectral imaging (Vis-NIR-HSI) techniques were applied on three different apple cultivars to compare their firmness prediction performances based on a large intra-variabi...

Exploring Radiomics Features Based on H&E Images as Potential Biomarkers for Evaluating Muscle Atrophy: A Preliminary Study.

Journal of imaging informatics in medicine
Radiomics features have been widely used as novel biomarkers in the diagnosis of various diseases, but whether radiomics features derived from hematoxylin and eosin (H&E) images can evaluate muscle atrophy has not been studied. Therefore, this study ...

Predictive modeling of co-infection in lupus nephritis using multiple machine learning algorithms.

Scientific reports
This study aimed to analyze peripheral blood lymphocyte subsets in lupus nephritis (LN) patients and use machine learning (ML) methods to establish an effective algorithm for predicting co-infection in LN. This study included 111 non-infected LN pati...

Machine learning and weighted gene co-expression network analysis identify a three-gene signature to diagnose rheumatoid arthritis.

Frontiers in immunology
BACKGROUND: Rheumatoid arthritis (RA) is a systemic immune-related disease characterized by synovial inflammation and destruction of joint cartilage. The pathogenesis of RA remains unclear, and diagnostic markers with high sensitivity and specificity...

Machine learning classification based on k-Nearest Neighbors for PolSAR data.

Anais da Academia Brasileira de Ciencias
In this work, we focus on obtaining insights of the performances of some well-known machine learning image classification techniques (k-NN, Support Vector Machine, randomized decision tree and one based on stochastic distances) for PolSAR (Polarimetr...