AIMC Topic: Diabetes Mellitus, Type 2
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Application of Machine Learning Methods to Predict Non-Alcoholic Steatohepatitis (NASH) in Non-Alcoholic Fatty Liver (NAFL) Patients.
AMIA ... Annual Symposium proceedings. AMIA Symposium
Dec 5, 2018
Non-alcoholic fatty liver disease (NAFLD) is the leading cause of chronic liver disease worldwide. NAFLD patients have excessive liver fat (steatosis), without other liver diseases and without excessive alcohol consumption. NAFLD consists of a spectr...
Disease Progression
Case-Control Studies
Cohort Studies
Diabetes Mellitus, Type 2
Fatty Liver
Female
Risk Factors
Humans
Aged
Male
Logistic Models
Middle Aged
Biomarkers
Liver Cirrhosis
Non-alcoholic Fatty Liver Disease
Electronic Health Records
Health Status
Hepatitis
Decision Trees
Alanine Transaminase
Supervised Machine Learning
Aspartate Aminotransferases
Liver Function Tests
Assessing urinary levels of IL-18, NGAL and albumin creatinine ratio in patients with diabetic nephropathy.
Diabetes & metabolic syndrome
Nov 10, 2018
AIMS: Diabetic nephropathy (DN) is a serious microvascular complication of a longstanding hyperglycemia. This study aims to evaluate whether urinary neutrophil gelatinase-associated lipocalin (NGAL) and urinary Interleukin-18 possess a better diagnos...
The association between serum uric acid to creatinine ratio and renal disease progression in type 2 diabetic patients in Chinese communities.
Journal of diabetes and its complications
Nov 3, 2018
AIMS: Serum uric acid (UA) increases in patients with kidney disease due to the impaired UA clearance. The present study sought to evaluate the association between UA/creatinine ratio (UA/Cr) and renal disease progression in patients with type 2 diab...
Circulating betatrophin in relation to metabolic, inflammatory parameters, and oxidative stress in patients with type 2 diabetes mellitus.
Diabetes & metabolic syndrome
Nov 3, 2018
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 ...
Stacked classifiers for individualized prediction of glycemic control following initiation of metformin therapy in type 2 diabetes.
Computers in biology and medicine
Oct 16, 2018
OBJECTIVE: Metformin is the preferred first-line medication for management of type 2 diabetes and prediabetes. However, over a third of patients experience primary or secondary therapeutic failure. We developed machine learning models to predict whic...
Digital Diabetes Data and Artificial Intelligence: A Time for Humility Not Hubris.
Journal of diabetes science and technology
Sep 5, 2018
In the future artificial intelligence (AI) will have the potential to improve outcomes diabetes care. With the creation of new sensors for physiological monitoring sensors and the introduction of smart insulin pens, novel data relationships based on ...
Data Collection
Racial Groups
Big Data
Decision Support Systems, Clinical
Diabetes Mellitus, Type 2
Phenotype
Genotype
Precision Medicine
Computational Biology
Language
Reproducibility of Results
Diabetes Mellitus, Type 1
Humans
Public Health
Decision Making
Artificial Intelligence
Healthcare Disparities
Access to Information
Ethnicity
Mixed effect machine learning: A framework for predicting longitudinal change in hemoglobin A1c.
Journal of biomedical informatics
Sep 4, 2018
Accurate and reliable prediction of clinical progression over time has the potential to improve the outcomes of chronic disease. The classical approach to analyzing longitudinal data is to use (generalized) linear mixed-effect models (GLMM). However,...
Identifying people at risk of developing type 2 diabetes: A comparison of predictive analytics techniques and predictor variables.
International journal of medical informatics
Aug 28, 2018
BACKGROUND: The present study aims to identify the patients at risk of type 2 diabetes (T2D). There is a body of literature that uses machine learning classification algorithms to predict development of T2D among patients. The current study compares ...
The involvement of phenolic-rich extracts from Galician autochthonous extra-virgin olive oils against the α-glucosidase and α-amylase inhibition.
Food research international (Ottawa, Ont.)
Aug 21, 2018
'Brava' and 'Mansa de Figueiredo' extra-virgin olive oils (EVOOs) are two varieties identified from north-western Spain. A systematic phenolic characterization of the studied oils was undertaken by LC-ESI-IT-MS. In addition, the role of dietary polyp...
Predicting diabetic retinopathy and identifying interpretable biomedical features using machine learning algorithms.
BMC bioinformatics
Aug 13, 2018
BACKGROUND: The risk factors of diabetic retinopathy (DR) were investigated extensively in the past studies, but it remains unknown which risk factors were more associated with the DR than others. If we can detect the DR related risk factors more acc...
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