AIMC Topic: Support Vector Machine

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Classification of fNIRS data with LDA and SVM: a proof-of-concept for application in infant studies.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Nov 1, 2021
This study presents the implementation of a within-subject classification method, based on the use of Linear Discriminant Analysis (LDA) and Support Vector Machines (SVM), for the classification of hemodynamic responses. Using a synthetic dataset tha...
Discriminant Analysis Humans Spectroscopy, Near-Infrared Hemodynamics Support Vector Machine Noise
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Decoding Human Cognitive Control Using Functional Connectivity of Local Field Potentials.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Nov 1, 2021
Many patients with mental illnesses characterized by impaired cognitive control have no relief from gold-standard clinical treatments resulting in a pressing need for new alternatives. This paper develops a neural decoder to detect task engagement in...
Brain Cognition Humans Support Vector Machine Task Performance and Analysis Algorithms
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Time-domain Mixup Source Data Augmentation of sEMGs for Motion Recognition towards Efficient Style Transfer Mapping.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Nov 1, 2021
Motion recognition based on surface electromyogram (sEMG) recorded from the forearm is attracting attention for its applicability because it easily integrates with wearable devices and has a high signal-to-noise ratio. Inter-subject variability and i...
Algorithms Support Vector Machine Electromyography Motion Humans Neural Networks, Computer
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Towards Interpretable Machine Learning in EEG Analysis.

Studies in health technology and informatics Sep 21, 2021
In this paper a machine learning model for automatic detection of abnormalities in electroencephalography (EEG) is dissected into parts, so that the influence of each part on the classification accuracy score can be examined. The most successful setu...
Support Vector Machine Wavelet Analysis Electroencephalography Signal Processing, Computer-Assisted Neural Networks, Computer Machine Learning Algorithms
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Machine learning approach to gene essentiality prediction: a review.

Briefings in bioinformatics Sep 2, 2021
UNLABELLED: Essential genes are critical for the growth and survival of any organism. The machine learning approach complements the experimental methods to minimize the resources required for essentiality assays. Previous studies revealed the need to...
Gene Ontology Caenorhabditis elegans Algorithms Humans Computational Biology Animals Machine Learning Support Vector Machine Gene Regulatory Networks Genes, Essential
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Integrating multi-scale neighbouring topologies and cross-modal similarities for drug-protein interaction prediction.

Briefings in bioinformatics Sep 2, 2021
MOTIVATION: Identifying the proteins that interact with drugs can reduce the cost and time of drug development. Existing computerized methods focus on integrating drug-related and protein-related data from multiple sources to predict candidate drug-t...
Pharmaceutical Preparations Humans Drug Development Support Vector Machine Proteins Protein Binding Computational Biology Machine Learning Models, Theoretical Algorithms Reproducibility of Results
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Identification of active molecules against Mycobacterium tuberculosis through machine learning.

Briefings in bioinformatics Sep 2, 2021
Tuberculosis (TB) is an infectious disease caused by Mycobacterium tuberculosis (Mtb) and it has been one of the top 10 causes of death globally. Drug-resistant tuberculosis (XDR-TB), extensively resistant to the commonly used first-line drugs, has e...
Reproducibility of Results Drug Discovery ROC Curve Support Vector Machine Area Under Curve Antitubercular Agents Humans Neural Networks, Computer Data Accuracy Tuberculosis, Multidrug-Resistant Models, Biological Mycobacterium tuberculosis
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Machine learning for phytopathology: from the molecular scale towards the network scale.

Briefings in bioinformatics Sep 2, 2021
With the increasing volume of high-throughput sequencing data from a variety of omics techniques in the field of plant-pathogen interactions, sorting, retrieving, processing and visualizing biological information have become a great challenge. Within...
Plant Pathology Receptors, Pattern Recognition Protein Interaction Mapping Disease Resistance Fungal Proteins Pathogen-Associated Molecular Pattern Molecules Bayes Theorem Support Vector Machine Host-Pathogen Interactions Bacterial Proteins Viral Proteins Protein Serine-Threonine Kinases Plants NLR Proteins Plant Diseases Gene Expression Regulation
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Comprehensive assessment of machine learning-based methods for predicting antimicrobial peptides.

Briefings in bioinformatics Sep 2, 2021
Antimicrobial peptides (AMPs) are a unique and diverse group of molecules that play a crucial role in a myriad of biological processes and cellular functions. AMP-related studies have become increasingly popular in recent years due to antimicrobial r...
Fungi Viruses Pore Forming Cytotoxic Proteins Bacteria Computational Biology Support Vector Machine Machine Learning Algorithms Databases, Factual Biofilms
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A survey on computational models for predicting protein-protein interactions.

Briefings in bioinformatics Sep 2, 2021
Proteins interact with each other to play critical roles in many biological processes in cells. Although promising, laboratory experiments usually suffer from the disadvantages of being time-consuming and labor-intensive. The results obtained are oft...
Support Vector Machine Databases, Genetic Proteins Humans Software Computational Biology Protein Interaction Domains and Motifs Saccharomyces cerevisiae Gene Ontology Protein Interaction Mapping Databases, Protein Models, Molecular Protein Conformation
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