AIMC Topic: Diabetes Mellitus

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An extensive analysis of various texture feature extractors to detect Diabetes Mellitus using facial specific regions.

Computers in biology and medicine Feb 22, 2017
INTRODUCTION: Researchers have recently discovered that Diabetes Mellitus can be detected through non-invasive computerized method. However, the focus has been on facial block color features. In this paper, we extensively study the effects of texture...
Reproducibility of Results Sensitivity and Specificity Colorimetry Humans Algorithms Image Interpretation, Computer-Assisted Pattern Recognition, Automated Photography Diabetes Mellitus Support Vector Machine Signal Processing, Computer-Assisted
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Improving Endpoint Detection to Support Automated Systematic Reviews.

AMIA ... Annual Symposium proceedings. AMIA Symposium Feb 10, 2017
Authors of biomedical articles use comparison sentences to communicate the findings of a study, and to compare the results of the current study with earlier studies. The Claim Framework defines a comparison claim as a sentence that includes at least ...
Review Literature as Topic Publications Linguistics Natural Language Processing Meta-Analysis as Topic Animals Diabetes Mellitus Support Vector Machine Humans Biomedical Research
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Diagnostic Method of Diabetes Based on Support Vector Machine and Tongue Images.

BioMed research international Jan 4, 2017
. The purpose of this research is to develop a diagnostic method of diabetes based on standardized tongue image using support vector machine (SVM). Tongue images of 296 diabetic subjects and 531 nondiabetic subjects were collected by the TDA-1 digit...
Tongue Middle Aged Female Diabetes Mellitus ROC Curve Humans Support Vector Machine Sensitivity and Specificity Image Processing, Computer-Assisted Principal Component Analysis Male
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Raman spectroscopy and PCA-SVM as a non-invasive diagnostic tool to identify and classify qualitatively glycated hemoglobin levels in vivo.

Journal of biophotonics Dec 23, 2016
In this study we identify and classify high and low levels of glycated hemoglobin (HbA1c) in healthy volunteers (HV) and diabetic patients (DP). Overall, 86 subjects were evaluated. The Raman spectrum was measured in three anatomical regions of the b...
Humans Algorithms Diabetes Mellitus Support Vector Machine Principal Component Analysis Sensitivity and Specificity Case-Control Studies Spectrum Analysis, Raman Glycated Hemoglobin
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A soft computing approach for diabetes disease classification.

Health informatics journal Nov 14, 2016
As a chronic disease, diabetes mellitus has emerged as a worldwide epidemic. The aim of this study is to classify diabetes disease by developing an intelligence system using machine learning techniques. Our method is developed through clustering, noi...
Algorithms Humans Diabetes Mellitus Machine Learning Models, Statistical
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An Improved Ensemble of Random Vector Functional Link Networks Based on Particle Swarm Optimization with Double Optimization Strategy.

PloS one Nov 11, 2016
For ensemble learning, how to select and combine the candidate classifiers are two key issues which influence the performance of the ensemble system dramatically. Random vector functional link networks (RVFL) without direct input-to-output links is o...
Humans Neural Networks, Computer Machine Learning Algorithms Brain Neoplasms Lung Diabetes Mellitus Wine Pattern Recognition, Automated
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Development of a plasminogen activator inhibitor (PAI-1) assay and comparison of plasma PAI-1 activity in hyperlipidemic/dyslipidemic dogs with either hyperadrenocorticism or diabetes mellitus, and healthy dogs.

Research in veterinary science Nov 8, 2016
Thrombosis is a serious complication of many canine diseases and may be related to decreased fibrinolytic potential. Plasminogen activator inhibitor-1 (PAI-1) is the key regulator of fibrinolysis with increased levels demonstrated in states of pro-th...
Plasminogen Activator Inhibitor 1 Hyperlipidemias Serologic Tests Dogs Dog Diseases Humans Animals Adrenocortical Hyperfunction Female Male Sensitivity and Specificity Diabetes Mellitus
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Activity Recognition for Diabetic Patients Using a Smartphone.

Journal of medical systems Oct 8, 2016
Diabetes is a disease that has to be managed through appropriate lifestyle. Technology can help with this, particularly when it is designed so that it does not impose an additional burden on the patient. This paper presents an approach that combines ...
Motor Activity Monitoring, Ambulatory Accelerometry Machine Learning Algorithms Geographic Information Systems Smartphone Electrocardiography Diabetes Mellitus Humans
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Building and analysis of protein-protein interactions related to diabetes mellitus using support vector machine, biomedical text mining and network analysis.

Computational biology and chemistry Sep 30, 2016
In order to understand the molecular mechanism underlying any disease, knowledge about the interacting proteins in the disease pathway is essential. The number of revealed protein-protein interactions (PPI) is still very limited compared to the avail...
Support Vector Machine Data Mining Protein Interaction Maps Diabetes Mellitus
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Confirming an integrated pathology of diabetes and its complications by molecular biomarker-target network analysis.

Molecular medicine reports Jul 7, 2016
Despite ongoing research into diabetes and its complications, the underlying molecular associations remain to be elucidated. The systematic identification of molecular interactions in associated diseases may be approached using a network analysis str...
Gene Regulatory Networks Signal Transduction Humans Diabetes Mellitus Neural Networks, Computer Metabolic Networks and Pathways Biomarkers Models, Biological Diabetes Complications
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