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Case-Control Studies

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Circulating betatrophin in relation to metabolic, inflammatory parameters, and oxidative stress in patients with type 2 diabetes mellitus.

Diabetes & metabolic syndrome
AIMS: Recently, it was suggested that betatrophin has a role in controlling pancreatic β cell proliferation and lipid metabolism, however, its role in human subjects has not been established yet. The predicting role of betatrophin and MDA along with ...

EEG may serve as a biomarker in Huntington's disease using machine learning automatic classification.

Scientific reports
Reliable markers measuring disease progression in Huntington's disease (HD), before and after disease manifestation, may guide a therapy aimed at slowing or halting disease progression. Quantitative electroencephalography (qEEG) may provide a quantif...

Increased risk of group B Streptococcus causing meningitis in infants with mannose-binding lectin deficiency.

Clinical microbiology and infection : the official publication of the European Society of Clinical Microbiology and Infectious Diseases
OBJECTIVES: To evaluate the association of mannose-binding lectin (MBL) deficiency with susceptibility and clinical features of group B Streptococcus (GBS) causing meningitis in Chinese infants.

Identification of Novel Genes in Human Airway Epithelial Cells associated with Chronic Obstructive Pulmonary Disease (COPD) using Machine-Based Learning Algorithms.

Scientific reports
The aim of this project was to identify candidate novel therapeutic targets to facilitate the treatment of COPD using machine-based learning (ML) algorithms and penalized regression models. In this study, 59 healthy smokers, 53 healthy non-smokers an...

Machine learning multivariate pattern analysis predicts classification of posttraumatic stress disorder and its dissociative subtype: a multimodal neuroimaging approach.

Psychological medicine
BACKGROUND: The field of psychiatry would benefit significantly from developing objective biomarkers that could facilitate the early identification of heterogeneous subtypes of illness. Critically, although machine learning pattern recognition method...

Multimodal MRI-based classification of migraine: using deep learning convolutional neural network.

Biomedical engineering online
BACKGROUND: Recently, deep learning technologies have rapidly expanded into medical image analysis, including both disease detection and classification. As far as we know, migraine is a disabling and common neurological disorder, typically characteri...

Recognition of Schizophrenia with Regularized Support Vector Machine and Sequential Region of Interest Selection using Structural Magnetic Resonance Imaging.

Scientific reports
Structural brain abnormalities in schizophrenia have been well characterized with the application of univariate methods to magnetic resonance imaging (MRI) data. However, these traditional techniques lack sensitivity and predictive value at the indiv...

Bounded Fuzzy Possibilistic Method Reveals Information about Lung Cancer through Analysis of Metabolomics.

IEEE/ACM transactions on computational biology and bioinformatics
Learning methods, such as conventional clustering and classification, have been applied in diagnosing diseases to categorize samples based on their features. Going beyond clustering samples, membership degrees represent to what degree each sample bel...

A Novel Morphological Analysis of DXA-DICOM Images by Artificial Neural Networks for Estimating Bone Mineral Density in Health and Disease.

Journal of clinical densitometry : the official journal of the International Society for Clinical Densitometry
One of the best methods for diagnosing bone disease in humans is site-specific and total bone mineral density (BMD) measurements by Dual-energy X-ray Absorptiometry (DXA) machines. The basic disadvantage of this technology is inconsistent BMD measure...