DiaTrend: A dataset from advanced diabetes technology to enable development of novel analytic solutions
Objective digital data is scarce yet needed in many domains to enable research that can
transform the standard of healthcare. While data from consumer-grade wearables and …
transform the standard of healthcare. While data from consumer-grade wearables and …
AWD-stacking: An enhanced ensemble learning model for predicting glucose levels
HZ Yang, Z Chen, J Huang, S Li - Plos one, 2024 - journals.plos.org
Accurate prediction of blood glucose levels is essential for type 1 diabetes optimizing insulin
therapy and minimizing complications in patients with type 1 diabetes. Using ensemble …
therapy and minimizing complications in patients with type 1 diabetes. Using ensemble …
[HTML][HTML] Advancing blood glucose prediction with neural architecture search and deep reinforcement learning for type 1 diabetics
For individuals with Type-1 diabetes mellitus, accurate prediction of future blood glucose
values is crucial to aid its regulation with insulin administration, tailored to the individual's …
values is crucial to aid its regulation with insulin administration, tailored to the individual's …
Investigating temporal patterns of glycemic control around holidays
Maintaining good glycemic control is a central part of diabetes care. However, it can be a
tedious task because many factors in daily living can affect glycemic control. To support …
tedious task because many factors in daily living can affect glycemic control. To support …
Hypoglycaemia prediction models with auto explanation
World-wide statistics show a considerable growth of the occurrence of different types of
Diabetes Mellitus, posing diverse challenges at many levels for public health policies. Some …
Diabetes Mellitus, posing diverse challenges at many levels for public health policies. Some …
Feature selection for multivariate time series via network pruning
In recent years, there has been an ever increasing amount of multivariate time series (MTS)
data in various domains, typically generated by a large family of sensors such as wearable …
data in various domains, typically generated by a large family of sensors such as wearable …
After-meal blood glucose level prediction for type-2 diabetic patients
Type 2 Diabetes, a metabolic disorder disease, is becoming a fast growing health crisis
worldwide. It reduces the quality of life, and increases mortality and health care costs unless …
worldwide. It reduces the quality of life, and increases mortality and health care costs unless …
[HTML][HTML] A personalized multitasking framework for real-time prediction of blood glucose levels in type 1 diabetes patients
H Yang, W Li, M Tian, Y Ren - Mathematical Biosciences and …, 2024 - aimspress.com
Real-time prediction of blood glucose levels (BGLs) in individuals with type 1 diabetes (T1D)
presents considerable challenges. Accordingly, we present a personalized multitasking …
presents considerable challenges. Accordingly, we present a personalized multitasking …
Forecasting with sparse but informative variables: a case study in predicting blood glucose
H Rubin-Falcone, J Lee, J Wiens - … of the AAAI Conference on Artificial …, 2023 - ojs.aaai.org
In time-series forecasting, future target values may be affected by both intrinsic and extrinsic
effects. When forecasting blood glucose, for example, intrinsic effects can be inferred from …
effects. When forecasting blood glucose, for example, intrinsic effects can be inferred from …
FedGlu: A personalized federated learning-based glucose forecasting algorithm for improved performance in glycemic excursion regions
Continuous glucose monitoring (CGM) devices provide real-time glucose monitoring and
timely alerts for glycemic excursions, improving glycemic control among patients with …
timely alerts for glycemic excursions, improving glycemic control among patients with …