AIMC Topic: Young Adult

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Bidirectional Recurrent Auto-Encoder for Photoplethysmogram Denoising.

IEEE journal of biomedical and health informatics Dec 5, 2018
Photoplethysmography (PPG) has become ubiquitous with the development of smart watches and the mobile healthcare market. However, PPG is vulnerable to various types of noises that are ever present in uncontrolled environments, and the key to obtainin...
Electrocardiography Signal Processing, Computer-Assisted Databases, Factual Young Adult Adult Male Photoplethysmography Humans Neural Networks, Computer Algorithms
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Exploring the interactions between serum free fatty acids and fecal microbiota in obesity through a machine learning algorithm.

Food research international (Ottawa, Ont.) Dec 5, 2018
Serum free fatty acids (FFA) are generally elevated in obesity. The gut microbiota is involved in the host energy metabolism through the regulation of body fat storage, and a link between diet, FFA and the intestinal microbiota seems to exist. Our ai...
Feces Young Adult Body Mass Index Adult Gastrointestinal Microbiome Male Obesity Middle Aged Diet Humans Docosahexaenoic Acids Machine Learning Eicosapentaenoic Acid Algorithms Faecalibacterium Female Fatty Acids, Nonesterified Aged Bifidobacterium
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Integrated machine learning pipeline for aberrant biomarker enrichment (i-mAB): characterizing clusters of differentiation within a compendium of systemic lupus erythematosus patients.

AMIA ... Annual Symposium proceedings. AMIA Symposium Dec 5, 2018
Clusters of differentiation () are cell surface biomarkers that denote key biological differences between cell types and disease state. CD-targeting therapeutic monoclonal antibodies () afford rich trans-disease repositioning opportunities. Within a ...
Adult Male Middle Aged Case-Control Studies Cell Adhesion Molecules Machine Learning Adolescent Child Ki-1 Antigen Biomarkers Cell Differentiation Sialic Acid Binding Ig-like Lectin 2 Female Humans Lupus Erythematosus, Systemic Aged Reference Values Young Adult Antigens, CD20
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SmartHeLP: Smartphone-based Hemoglobin Level Prediction Using an Artificial Neural Network.

AMIA ... Annual Symposium proceedings. AMIA Symposium Dec 5, 2018
Blood hemoglobin level (Hgb) measurement has a vital role in the diagnosis, evaluation, and management of numerous diseases. We describe the use of smartphone video imaging and an artificial neural network (ANN) system to estimate Hgb levels non-inva...
Humans Neural Networks, Computer Female Spectrum Analysis Smartphone Young Adult Regression Analysis Adult Hemoglobins Sensitivity and Specificity Video Recording Male Datasets as Topic Middle Aged
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Improving the calling of non-invasive prenatal testing on 13-/18-/21-trisomy by support vector machine discrimination.

PloS one Dec 5, 2018
With the advance of next-generation sequencing (NGS) technologies, non-invasive prenatal testing (NIPT) has been developed and employed in fetal aneuploidy screening on 13-/18-/21-trisomies through detecting cell-free fetal DNA (cffDNA) in maternal b...
False Negative Reactions False Positive Reactions Humans Prenatal Diagnosis Trisomy 13 Syndrome Machine Learning Trisomy 18 Syndrome Retrospective Studies Sequence Analysis, DNA Pregnancy Diagnosis, Differential Female Genetic Testing Young Adult High-Throughput Nucleotide Sequencing Adult Down Syndrome Diagnosis, Computer-Assisted Support Vector Machine
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Combination of high-frequency SSVEP-based BCI and computer vision for controlling a robotic arm.

Journal of neural engineering Dec 3, 2018
OBJECTIVE: Recent attempts in developing brain-computer interface (BCI)-controlled robots have shown the potential of this area in the field of assistive robots. However, implementing the process of picking and placing objects using a BCI-controlled ...
Healthy Volunteers Arm Visual Prosthesis Adult Humans Brain-Computer Interfaces Fixation, Ocular Biomechanical Phenomena Algorithms Evoked Potentials, Visual Male Female Photic Stimulation Young Adult Robotics Electroencephalography
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Learning Spatial-Spectral-Temporal EEG Features With Recurrent 3D Convolutional Neural Networks for Cross-Task Mental Workload Assessment.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Dec 3, 2018
Mental workload assessment is essential for maintaining human health and preventing accidents. Most research on this issue is limited to a single task. However, cross-task assessment is indispensable for extending a pre-trained model to new workload ...
Humans Neural Networks, Computer Machine Learning Workload Wavelet Analysis Mathematics Space Perception Mental Processes Algorithms Young Adult Adult Male Electroencephalography
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In vitro activity of tedizolid and other comparator drugs in methicillin-resistant Staphylococcus aureus isolates in skin and soft tissue infections in seven Colombian hospitals.

Biomedica : revista del Instituto Nacional de Salud Dec 1, 2018
Introduction: Methicillin-resistant Staphylococcus aureus (MRSA) causes severe skin and soft tissue infections in hospitals and, more recently, in the community. Tedizolid is a new second-generation oxazolidinone derivative having greater in vitro po...
Adolescent Staphylococcal Skin Infections Humans Methicillin-Resistant Staphylococcus aureus Anti-Bacterial Agents Colombia Oxazolidinones Soft Tissue Infections Tetrazoles Adult Prospective Studies Male Female Middle Aged Aged Hospitals Aged, 80 and over Microbial Sensitivity Tests Young Adult
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Predicting response to somatostatin analogues in acromegaly: machine learning-based high-dimensional quantitative texture analysis on T2-weighted MRI.

European radiology Nov 30, 2018
OBJECTIVE: To investigate the value of machine learning (ML)-based high-dimensional quantitative texture analysis (qTA) on T2-weighted magnetic resonance imaging (MRI) in predicting response to somatostatin analogues (SA) in acromegaly patients with ...
Acromegaly Somatostatin ROC Curve Magnetic Resonance Imaging Pituitary Neoplasms Adenoma Predictive Value of Tests Humans Machine Learning Algorithms Retrospective Studies Female Reproducibility of Results Young Adult Adult Male Middle Aged
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QuickNAT: A fully convolutional network for quick and accurate segmentation of neuroanatomy.

NeuroImage Nov 29, 2018
Whole brain segmentation from structural magnetic resonance imaging (MRI) is a prerequisite for most morphological analyses, but is computationally intense and can therefore delay the availability of image markers after scan acquisition. We introduce...
Humans Neural Networks, Computer Brain Deep Learning Image Processing, Computer-Assisted Magnetic Resonance Imaging Datasets as Topic Neuroimaging Aged Aged, 80 and over Young Adult Adult Middle Aged Neuroanatomy
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