AIMC Topic: Blood Glucose
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Use of Machine Learning and Hybrid Closed Loop Insulin Delivery at Diabetes Camps.
Diabetes technology & therapeutics
Jun 15, 2020
Improving blood glucose level predictability using machine learning.
Diabetes/metabolism research and reviews
Jun 14, 2020
This study was designed to improve blood glucose level predictability and future hypoglycemic and hyperglycemic event alerts through a novel patient-specific supervised-machine-learning (SML) analysis of glucose level based on a continuous-glucose-mo...
Comparison of Machine Learning Methods and Conventional Logistic Regressions for Predicting Gestational Diabetes Using Routine Clinical Data: A Retrospective Cohort Study.
Journal of diabetes research
Jun 12, 2020
BACKGROUND: Gestational diabetes mellitus (GDM) contributes to adverse pregnancy and birth outcomes. In recent decades, extensive research has been devoted to the early prediction of GDM by various methods. Machine learning methods are flexible predi...
Logistic Models
Decision Trees
Glycated Hemoglobin
Cholesterol
Humans
Pregnancy in Obesity
Machine Learning
Uric Acid
Young Adult
Diabetes, Gestational
Retrospective Studies
Routinely Collected Health Data
Lipoproteins, HDL
Adult
Pregnancy
Maternal Age
Blood Glucose
Female
Triglycerides
Cohort Studies
Reproducibility of Results
Clinical Decision Rules
Artificial Intelligence in Decision Support Systems for Type 1 Diabetes.
Sensors (Basel, Switzerland)
Jun 5, 2020
Type 1 diabetes (T1D) is a chronic health condition resulting from pancreatic beta cell dysfunction and insulin depletion. While automated insulin delivery systems are now available, many people choose to manage insulin delivery manually through insu...
An artificial intelligence decision support system for the management of type 1 diabetes.
Nature metabolism
Jun 1, 2020
Type 1 diabetes (T1D) is characterized by pancreatic beta cell dysfunction and insulin depletion. Over 40% of people with T1D manage their glucose through multiple injections of long-acting basal and short-acting bolus insulin, so-called multiple dai...
Artificial intelligence and network pharmacology based investigation of pharmacological mechanism and substance basis of Xiaokewan in treating diabetes.
Pharmacological research
May 25, 2020
Xiaokewan is a typical Traditional Chinese medicine (TCM) for diabetes and contains various natural chemicals, such as lignans, flavonoids, saponins, polysaccharides, and western medicine glibenclamide. In the current study, a highly efficient system...
Chromatography, High Pressure Liquid
Tandem Mass Spectrometry
Data Mining
Spectrometry, Mass, Electrospray Ionization
Animals, Genetically Modified
Disease Models, Animal
Drugs, Chinese Herbal
Workflow
Zebrafish
Animals
Male
Blood Glucose
Protein Interaction Maps
Gene Regulatory Networks
Systems Biology
Rats, Wistar
Hypoglycemic Agents
Diabetes Mellitus
Artificial Intelligence
Biomarkers
Predicting the Risk of Inpatient Hypoglycemia With Machine Learning Using Electronic Health Records.
Diabetes care
Apr 29, 2020
OBJECTIVE: We analyzed data from inpatients with diabetes admitted to a large university hospital to predict the risk of hypoglycemia through the use of machine learning algorithms.
Data science and machine learning in anesthesiology.
Korean journal of anesthesiology
Mar 25, 2020
Machine learning (ML) is revolutionizing anesthesiology research. Unlike classical research methods that are largely inference-based, ML is geared more towards making accurate predictions. ML is a field of artificial intelligence concerned with devel...
A Noninvasive Glucose Monitoring SoC Based on Single Wavelength Photoplethysmography.
IEEE transactions on biomedical circuits and systems
Mar 9, 2020
Conventional glucose monitoring methods for the growing numbers of diabetic patients around the world are invasive, painful, costly and, time-consuming. Complications aroused due to the abnormal blood sugar levels in diabetic patients have created th...
Predicting Nocturnal Hypoglycemia from Continuous Glucose Monitoring Data with Extended Prediction Horizon.
AMIA ... Annual Symposium proceedings. AMIA Symposium
Mar 4, 2020
Nocturnal hypoglycemia is a serious complication of insulin-treated diabetes, which commonly goes undetected. Continuous glucose monitoring (CGM) devices have enabled prediction of impending nocturnal hypoglycemia, however, prior efforts have been li...
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