AIMC Topic: Support Vector Machine

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Multi-band spatial feature extraction and classification for motor imaging EEG signals based on OSFBCSP-GAO-SVM model : EEG signal processing.

Medical & biological engineering & computing Feb 23, 2023
Electroencephalogram (EEG) is a non-stationary random signal with strong background noise, which makes its feature extraction difficult and recognition rate low. This paper presents a feature extraction and classification model of motor imagery EEG s...
Signal Processing, Computer-Assisted Brain-Computer Interfaces Electroencephalography Imagination Support Vector Machine Algorithms
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Phonocardiogram transfer learning-based CatBoost model for diastolic dysfunction identification using multiple domain-specific deep feature fusion.

Computers in biology and medicine Feb 20, 2023
Left ventricular diastolic dyfunction detection is particularly important in cardiac function screening. This paper proposed a phonocardiogram (PCG) transfer learning-based CatBoost model to detect diastolic dysfunction noninvasively. The Short-Time ...
Support Vector Machine Neural Networks, Computer Machine Learning Random Forest Fourier Analysis
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Application of machine learning algorithms in thermal images for an automatic classification of lumbar sympathetic blocks.

Journal of thermal biology Feb 17, 2023
PURPOSE: There are no previous studies developing machine learning algorithms in the classification of lumbar sympathetic blocks (LSBs) performance using infrared thermography data. The objective was to assess the performance of different machine lea...
Humans Algorithms Machine Learning Random Forest Support Vector Machine
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Learning Relationships Between Chemical and Physical Stability for Peptide Drug Development.

Pharmaceutical research Feb 16, 2023
PURPOSE OR OBJECTIVE: Chemical and physical stabilities are two key features considered in pharmaceutical development. Chemical stability is typically reported as a combination of potency and degradation product. Moreover, fluorescent reporter Thiofl...
Machine Learning Support Vector Machine Neural Networks, Computer Random Forest
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Construction of a new smooth support vector machine model and its application in heart disease diagnosis.

PloS one Feb 9, 2023
Support vector machine (SVM) is a new machine learning method developed from statistical learning theory. Since the objective function of the unconstrained SVM model is a non-smooth function, a lot of fast optimization algorithms can't be used to fin...
Support Vector Machine Machine Learning Humans Heart Diseases Algorithms
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NeuroPpred-SVM: A New Model for Predicting Neuropeptides Based on Embeddings of BERT.

Journal of proteome research Feb 7, 2023
Neuropeptides play pivotal roles in different physiological processes and are related to different kinds of diseases. Identification of neuropeptides is of great benefit for studying the mechanism of these physiological processes and the treatment of...
Support Vector Machine Algorithms ROC Curve Area Under Curve Neuropeptides
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Mapping Pu'er tea plantations from GF-1 images using Object-Oriented Image Analysis (OOIA) and Support Vector Machine (SVM).

PloS one Feb 7, 2023
Tea is the most popular drink worldwide, and China is the largest producer of tea. Therefore, tea is an important commercial crop in China, playing a significant role in domestic and foreign markets. It is necessary to make accurate and timely maps o...
Tea China Support Vector Machine
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An Efficient Feature Selection Algorithm for Gene Families Using NMF and ReliefF.

Genes Feb 6, 2023
Gene families, which are parts of a genome's information storage hierarchy, play a significant role in the development and diversity of multicellular organisms. Several studies have focused on the characteristics of gene families, such as function, h...
Oligonucleotide Array Sequence Analysis Databases, Factual Support Vector Machine Algorithms
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Forecasting the energy intensity of industrial sector in China based on FCM-RS-SVM model.

Environmental science and pollution research international Feb 1, 2023
Analysis of industrial energy intensity is greatly significant in China specifically from the perspective of sector heterogeneity due to considerably different levels of energy utilization in various industrial sub-sectors. This study proposes a new ...
Support Vector Machine Carbon China Economic Development Manufacturing Industry Industry Carbon Dioxide
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IGPred-HDnet: Prediction of Immunoglobulin Proteins Using Graphical Features and the Hierarchal Deep Learning-Based Approach.

Computational intelligence and neuroscience Jan 25, 2023
. Immunoglobulin proteins (IGP) (also called antibodies) are glycoproteins that act as B-cell receptors against external or internal antigens like viruses and bacteria. IGPs play a significant role in diverse cellular processes ranging from adhesion ...
Proteins Immunoglobulins Support Vector Machine Machine Learning Deep Learning Computational Biology Algorithms
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