AIMC Topic: Humans

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Classification of epileptic EEG recordings using signal transforms and convolutional neural networks.

Computers in biology and medicine Apr 25, 2019
This paper describes the analysis of a deep neural network for the classification of epileptic EEG signals. The deep learning architecture is made up of two convolutional layers for feature extraction and three fully-connected layers for classificati...
Humans Deep Learning Signal Processing, Computer-Assisted Electroencephalography Epilepsy
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Neural network and support vector machine for the prediction of chronic kidney disease: A comparative study.

Computers in biology and medicine Apr 25, 2019
This paper aims to assist in the prevention of Chronic Kidney Disease (CKD) by utilizing machine learning techniques to diagnose CKD at an early stage. Kidney diseases are disorders that disrupt the normal function of the kidney. As the percentage of...
Humans Neural Networks, Computer Support Vector Machine Diagnosis, Computer-Assisted Renal Insufficiency, Chronic
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Machine learning for phenotyping opioid overdose events.

Journal of biomedical informatics Apr 25, 2019
OBJECTIVE: To develop machine learning models for classifying the severity of opioid overdose events from clinical data.
Drug Overdose Machine Learning Phenotype Severity of Illness Index Analgesics, Opioid Electronic Health Records Humans
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Multiclass Support Matrix Machines by Maximizing the Inter-Class Margin for Single Trial EEG Classification.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Apr 25, 2019
Accurate classification of Electroencephalogram (EEG) signals plays an important role in diagnoses of different type of mental activities. One of the most important challenges, associated with classification of EEG signals is how to design an efficie...
Machine Learning Algorithms Humans Signal Processing, Computer-Assisted Brain-Computer Interfaces Mental Processes Support Vector Machine Electroencephalography
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Reporting and connecting cell type names and gating definitions through ontologies.

BMC bioinformatics Apr 25, 2019
BACKGROUND: Human immunology studies often rely on the isolation and quantification of cell populations from an input sample based on flow cytometry and related techniques. Such techniques classify cells into populations based on the detection of a p...
Immune System Protein Subunits Proteins Humans Biological Ontologies Databases, Factual
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OSCI: standardized stem cell ontology representation and use cases for stem cell investigation.

BMC bioinformatics Apr 25, 2019
BACKGROUND: Stem cells and stem cell lines are widely used in biomedical research. The Cell Ontology (CL) and Cell Line Ontology (CLO) are two community-based OBO Foundry ontologies in the domains of in vivo cells and in vitro cell line cells, respec...
Biological Ontologies Animals Humans Stem Cells Biomedical Research
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Cells in ExperimentaL Life Sciences (CELLS-2018): capturing the knowledge of normal and diseased cells with ontologies.

BMC bioinformatics Apr 25, 2019
Cell cultures and cell lines are widely used in life science experiments. In conjunction with the 2018 International Conference on Biomedical Ontology (ICBO-2018), the 2nd International Workshop on Cells in ExperimentaL Life Science (CELLS-2018) focu...
Humans Congresses as Topic Research Biological Ontologies Biological Science Disciplines
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An ontology for representing hematologic malignancies: the cancer cell ontology.

BMC bioinformatics Apr 25, 2019
BACKGROUND: Within the cancer domain, ontologies play an important role in the integration and annotation of data in order to support numerous biomedical tools and applications. This work seeks to leverage existing standards in immunophenotyping cell...
Immunophenotyping Biological Ontologies Humans Cell Line, Tumor Neoplastic Stem Cells Machine Learning Hematologic Neoplasms
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The cell line ontology-based representation, integration and analysis of cell lines used in China.

BMC bioinformatics Apr 25, 2019
BACKGROUND: The Chinese National Infrastructure of Cell Line stores and distributes cell lines for biomedical research in China. This study aims to represent and integrate the information of NICR cell lines into the community-based Cell Line Ontology...
Databases, Factual Biomedical Research Humans Cell Line China Biological Ontologies User-Computer Interface
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Regression Algorithm of Bone Age Estimation of Knee-joint Based on Principal Component Analysis and Support Vector Machine.

Fa yi xue za zhi Apr 25, 2019
Objective To establish a regression algorithm model that applies to bone age estimation of Xinjiang Uygur adolescents with machine learning methods such as histogram of oriented gradient （HOG）, local binary patterns （LBP）, support vector machine （SVM...
Asian People Age Determination by Skeleton Image Processing, Computer-Assisted Support Vector Machine Principal Component Analysis Knee Joint China Adolescent Adult Male Humans Machine Learning Female Young Adult Algorithms
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