[HTML][HTML] Data-driven modeling and prediction of blood glucose dynamics: Machine learning applications in type 1 diabetes
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 …
glucose (BG) regulation that might result in short and long-term health complications and …
A review of personalized blood glucose prediction strategies for T1DM patients
This paper presents a methodological review of models for predicting blood glucose (BG)
concentration, risks and BG events. The surveyed models are classified into three …
concentration, risks and BG events. The surveyed models are classified into three …
A comprehensive review on smart decision support systems for health care
Medical activity requires responsibility not only based on knowledge and clinical skills, but
also in managing a vast amount of information related to patient care. It is through the …
also in managing a vast amount of information related to patient care. It is through the …
Artificial intelligence and machine learning for improving glycemic control in diabetes: best practices, pitfalls and opportunities
Objective: Artificial intelligence and machine learning are transforming many fields including
medicine. In diabetes, robust biosensing technologies and automated insulin delivery …
medicine. In diabetes, robust biosensing technologies and automated insulin delivery …
Design and development of diabetes management system using machine learning
RA Sowah, AA Bampoe-Addo… - … of telemedicine and …, 2020 - Wiley Online Library
This paper describes the design and implementation of a software system to improve the
management of diabetes using a machine learning approach and to demonstrate and …
management of diabetes using a machine learning approach and to demonstrate and …
[HTML][HTML] Forecasting of glucose levels and hypoglycemic events: head-to-head comparison of linear and nonlinear data-driven algorithms based on continuous …
In type 1 diabetes management, the availability of algorithms capable of accurately
forecasting future blood glucose (BG) concentrations and hypoglycemic episodes could …
forecasting future blood glucose (BG) concentrations and hypoglycemic episodes could …
An ARIMA model with adaptive orders for predicting blood glucose concentrations and hypoglycemia
J Yang, L Li, Y Shi, X Xie - IEEE journal of biomedical and …, 2018 - ieeexplore.ieee.org
The continuous glucose monitoring system is an effective tool, which enables the users to
monitor their blood glucose (BG) levels. Based on the continuous glucose monitoring (CGM) …
monitor their blood glucose (BG) levels. Based on the continuous glucose monitoring (CGM) …
[PDF][PDF] Comparison of statistical logistic regression and random forest machine learning techniques in predicting diabetes
T Daghistani, R Alshammari - Journal of Advances in Information Technology …, 2020 - jait.us
Diabetes is one of the global concerns in the healthcare domain and one of the leading
challenges locally in Saudi Arabia. The prevalence of diabetes is anticipated to rise; early …
challenges locally in Saudi Arabia. The prevalence of diabetes is anticipated to rise; early …
Methylglyoxal–an emerging biomarker for diabetes mellitus diagnosis and its detection methods
LR Bhat, S Vedantham, UM Krishnan… - Biosensors and …, 2019 - Elsevier
Diabetes Mellitus (DM) is one among the supreme metabolic issues observed in history
since 3000 BCE and has gained much interest recently due to the increasing number of …
since 3000 BCE and has gained much interest recently due to the increasing number of …
An ontology-based interpretable fuzzy decision support system for diabetes diagnosis
Diabetes is a serious chronic disease. The importance of clinical decision support systems
(CDSSs) to diagnose diabetes has led to extensive research efforts to improve the accuracy …
(CDSSs) to diagnose diabetes has led to extensive research efforts to improve the accuracy …