AIMC Topic: Insulin
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Predicting long-term type 2 diabetes with support vector machine using oral glucose tolerance test.
PloS one
Dec 11, 2019
Diabetes is a large healthcare burden worldwide. There is substantial evidence that lifestyle modifications and drug intervention can prevent diabetes, therefore, an early identification of high risk individuals is important to design targeted preven...
Glycemic-aware metrics and oversampling techniques for predicting blood glucose levels using machine learning.
PloS one
Dec 2, 2019
Techniques using machine learning for short term blood glucose level prediction in patients with Type 1 Diabetes are investigated. This problem is significant for the development of effective artificial pancreas technology so accurate alerts (e.g. hy...
Comparing information extraction techniques for low-prevalence concepts: The case of insulin rejection by patients.
Journal of biomedical informatics
Oct 13, 2019
OBJECTIVE: To comparatively evaluate a range of Natural Language Processing (NLP) approaches for Information Extraction (IE) of low-prevalence concepts in clinical notes on the example of decline of insulin therapy recommendation by patients.
Predicting short- and long-term glycated haemoglobin response after insulin initiation in patients with type 2 diabetes mellitus using machine-learning algorithms.
Diabetes, obesity & metabolism
Sep 30, 2019
AIM: To assess the potential of supervised machine-learning techniques to identify clinical variables for predicting short-term and long-term glycated haemoglobin (HbA1c) response after insulin treatment initiation in patients with type 2 diabetes me...
Predicting Quality of Overnight Glycaemic Control in Type 1 Diabetes Using Binary Classifiers.
IEEE journal of biomedical and health informatics
Sep 13, 2019
In type 1 diabetes management, maintaining nocturnal blood glucose within target range can be challenging. Although semi-automatic systems to modulate insulin pump delivery, such as low-glucose insulin suspension and the artificial pancreas, are star...
Prediction of metabolic status of dairy cows in early lactation with on-farm cow data and machine learning algorithms.
Journal of dairy science
Aug 30, 2019
Metabolic status of dairy cows in early lactation can be evaluated using the concentrations of plasma β-hydroxybutyrate (BHB), free fatty acids (FFA), glucose, insulin, and insulin-like growth factor 1 (IGF-1). These plasma metabolites and metabolic ...
The parameter Houlihan: A solution to high-throughput identifiability indeterminacy for brutally ill-posed problems.
Mathematical biosciences
Aug 24, 2019
One way to interject knowledge into clinically impactful forecasting is to use data assimilation, a nonlinear regression that projects data onto a mechanistic physiologic model, instead of a set of functions, such as neural networks. Such regressions...
Data-driven modeling and prediction of blood glucose dynamics: Machine learning applications in type 1 diabetes.
Artificial intelligence in medicine
Jul 26, 2019
BACKGROUND: Diabetes mellitus (DM) is a metabolic disorder that causes abnormal blood glucose (BG) regulation that might result in short and long-term health complications and even death if not properly managed. Currently, there is no cure for diabet...
Minimizing postprandial hypoglycemia in Type 1 diabetes patients using multiple insulin injections and capillary blood glucose self-monitoring with machine learning techniques.
Computer methods and programs in biomedicine
Jun 27, 2019
BACKGROUND: Diabetic patients treated with intensive insulin therapies require a tight glycemic control and may benefit from advanced tools to predict blood glucose (BG) concentration levels and hypo/hyperglycemia events. Prediction systems using mac...
Hypoglycemic Agents
Bayes Theorem
Hypoglycemia
Postprandial Period
Blood Glucose Self-Monitoring
False Positive Reactions
Normal Distribution
Insulin Infusion Systems
Capillaries
Middle Aged
Blood Glucose
Machine Learning
Insulin
Algorithms
Humans
Diabetes Mellitus, Type 1
Computer Simulation
Reproducibility of Results
Retrospective Studies
Adult
Female
Sensitivity and Specificity
Male
Recognition of early and late stages of bladder cancer using metabolites and machine learning.
Metabolomics : Official journal of the Metabolomic Society
Jun 20, 2019
INTRODUCTION: Bladder cancer (BCa) is one of the most common and aggressive cancers. It is the sixth most frequently occurring cancer in men and its rate of occurrence increases with age. The current method of BCa diagnosis includes a cystoscopy and ...
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