AIMC Topic: Diabetes Mellitus, Type 2
Clear Filters Showing 211 to 220 of 424 articles
Combinatorial K-Means Clustering as a Machine Learning Tool Applied to Diabetes Mellitus Type 2.
International journal of environmental research and public health
Feb 17, 2021
A new original procedure based on k-means clustering is designed to find the most appropriate clinical variables able to efficiently separate into groups similar patients diagnosed with diabetes mellitus type 2 (DMT2) and underlying diseases (arteria...
The Use of Machine Learning Techniques to Determine the Predictive Value of Inflammatory Biomarkers in the Development of Type 2 Diabetes Mellitus.
Metabolic syndrome and related disorders
Feb 16, 2021
Certain inflammatory biomarkers, such as interleukin-6, interleukin-1, C-reactive protein (CRP), and fibrinogen, are prototypical acute-phase parameters that can also be predictors of cardiovascular disease. However, this inflammatory response can a...
Systems Approach to Pathogenic Mechanism of Type 2 Diabetes and Drug Discovery Design Based on Deep Learning and Drug Design Specifications.
International journal of molecular sciences
Dec 26, 2020
In this study, we proposed a systems biology approach to investigate the pathogenic mechanism for identifying significant biomarkers as drug targets and a systematic drug discovery strategy to design a potential multiple-molecule targeting drug for t...
Potential predictors of type-2 diabetes risk: machine learning, synthetic data and wearable health devices.
BMC bioinformatics
Dec 14, 2020
BACKGROUND: The aim of a recent research project was the investigation of the mechanisms involved in the onset of type 2 diabetes in the absence of familiarity. This has led to the development of a computational model that recapitulates the aetiology...
A Universal Approximation Result for Difference of Log-Sum-Exp Neural Networks.
IEEE transactions on neural networks and learning systems
Nov 30, 2020
We show that a neural network whose output is obtained as the difference of the outputs of two feedforward networks with exponential activation function in the hidden layer and logarithmic activation function in the output node, referred to as log-su...
PredAmyl-MLP: Prediction of Amyloid Proteins Using Multilayer Perceptron.
Computational and mathematical methods in medicine
Nov 20, 2020
Amyloid is generally an aggregate of insoluble fibrin; its abnormal deposition is the pathogenic mechanism of various diseases, such as Alzheimer's disease and type II diabetes. Therefore, accurately identifying amyloid is necessary to understand its...
Type IV Collagen 7S Is the Most Accurate Test For Identifying Advanced Fibrosis in NAFLD With Type 2 Diabetes.
Hepatology communications
Nov 16, 2020
This study aimed to examine whether the diagnostic accuracy of four noninvasive tests (NITs) for detecting advanced fibrosis in nonalcoholic fatty liver disease (NAFLD) is maintained or is inferior to with or without the presence of type 2 diabetes. ...
Host variables confound gut microbiota studies of human disease.
Nature
Nov 4, 2020
Low concordance between studies that examine the role of microbiota in human diseases is a pervasive challenge that limits the capacity to identify causal relationships between host-associated microorganisms and pathology. The risk of obtaining false...
Alcohol Drinking
Disease
Life Style
Confounding Factors, Epidemiologic
Young Adult
RNA, Ribosomal, 16S
Adult
Residence Characteristics
Male
Diabetes Mellitus, Type 2
Area Under Curve
Middle Aged
Body Mass Index
Gastrointestinal Motility
Diet
Data Analysis
Gastrointestinal Microbiome
Humans
Case-Control Studies
Female
Machine Learning
Feces
Aged
ROC Curve
Aged, 80 and over
Predicting Diabetic Neuropathy Risk Level Using Artificial Neural Network and Clinical Parameters of Subjects With Diabetes.
Journal of diabetes science and technology
Oct 22, 2020
BACKGROUND: A risk assessment tool has been developed for automated estimation of level of neuropathy based on the clinical characteristics of patients. The smart tool is based on risk factors for diabetic neuropathy, which utilizes vibration percept...
Machine Learning Approaches Reveal Metabolic Signatures of Incident Chronic Kidney Disease in Individuals With Prediabetes and Type 2 Diabetes.
Diabetes
Oct 6, 2020
Early and precise identification of individuals with prediabetes and type 2 diabetes (T2D) at risk for progressing to chronic kidney disease (CKD) is essential to prevent complications of diabetes. Here, we identify and evaluate prospective metabolit...
Don't Miss the Future of Medicine
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.
Subscribe NowPopular Topics
- Machine Learning 32021
- Neural Networks, Computer 30231
- Algorithms 27405
- Deep Learning 26912
- Artificial Intelligence 24844
- Robotics 13389
- Image Processing, Computer-Assisted 9738
- Retrospective Studies 9346
- Magnetic Resonance Imaging 6347
- Reproducibility of Results 5670
- Tomography, X-Ray Computed 4866
- Support Vector Machine 4771
- Computational Biology 4333
- Brain 4129
- Computer Simulation 3935
Recent Journals
- Scientific reports 6800
- Sensors (Basel, Switzerland) 4794
- PloS one 4210
- Neural networks : the official journal of the International Neural Network Society 3026
- Computational intelligence and neuroscience 1931
- Computers in biology and medicine 1916
- Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference 1686
- Studies in health technology and informatics 1378
- IEEE journal of biomedical and health informatics 1172
- Journal of chemical information and modeling 1066
- Nature communications 1047
- Computer methods and programs in biomedicine 883
- Bioinformatics (Oxford, England) 874
- Journal of medical Internet research 864
- Briefings in bioinformatics 853