AIMC Topic: Hypoglycemia
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Machine Learning Techniques for Hypoglycemia Prediction: Trends and Challenges.
Sensors (Basel, Switzerland)
Jan 14, 2021
(1) Background: the use of machine learning techniques for the purpose of anticipating hypoglycemia has increased considerably in the past few years. Hypoglycemia is the drop in blood glucose below critical levels in diabetic patients. This may cause...
Development and Validation of a Machine Learning Model to Predict Near-Term Risk of Iatrogenic Hypoglycemia in Hospitalized Patients.
JAMA network open
Jan 4, 2021
IMPORTANCE: Accurate clinical decision support tools are needed to identify patients at risk for iatrogenic hypoglycemia, a potentially serious adverse event, throughout hospitalization.
Artificial Intelligence (AI) based machine learning models predict glucose variability and hypoglycaemia risk in patients with type 2 diabetes on a multiple drug regimen who fast during ramadan (The PROFAST - IT Ramadan study).
Diabetes research and clinical practice
Aug 26, 2020
OBJECTIVE: To develop a machine-based algorithm from clinical and demographic data, physical activity and glucose variability to predict hyperglycaemic and hypoglycaemic excursions in patients with type 2 diabetes on multiple glucose lowering therapi...
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...
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...
Natural Language Processing Improves Detection of Nonsevere Hypoglycemia in Medical Records Versus Coding Alone in Patients With Type 2 Diabetes but Does Not Improve Prediction of Severe Hypoglycemia Events: An Analysis Using the Electronic Medical Record in a Large Health System.
Diabetes care
May 15, 2020
OBJECTIVE: To determine if natural language processing (NLP) improves detection of nonsevere hypoglycemia (NSH) in patients with type 2 diabetes and no NSH documentation by diagnosis codes and to measure if NLP detection improves the prediction of fu...
International Classification of Diseases
Community Health Planning
Clinical Decision Rules
Predictive Value of Tests
Natural Language Processing
Hypoglycemia
Information Storage and Retrieval
Aged
Aged, 80 and over
Young Adult
Adult
Male
Middle Aged
Severity of Illness Index
Diabetes Mellitus, Type 2
United States
Humans
Algorithms
Electronic Health Records
Female
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.
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...
Precision Medicine and Artificial Intelligence: A Pilot Study on Deep Learning for Hypoglycemic Events Detection based on ECG.
Scientific reports
Jan 13, 2020
Tracking the fluctuations in blood glucose levels is important for healthy subjects and crucial diabetic patients. Tight glucose monitoring reduces the risk of hypoglycemia, which can result in a series of complications, especially in diabetic patien...
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...
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