Aug 24, 2019 · We conclude that multi-signal Gaussian Processes can improve blood glucose prediction by using contextual information and may provide a significant shift in ...
Clinical Relevance We evaluate how contextual information can be used in a blood glucose level prediction. Though several years of medical research have shown ...
We find this approach outperforms common methods for multi-variate data, as well as using the blood glucose values in isolation. Given a robust evaluation ...
It is concluded that multi-signal Gaussian Processes can improveBlood glucose prediction by using contextual information and may provide a significant shift ...
Sep 10, 2024 · While it is reported that glucose concentration is sensitive to social context such as mood, physical activity, stress, diet, alongside the ...
People also ask
How do you improve blood glucose levels?
What do you use to estimate blood glucose level?
What is the most common method used to quantify blood glucose levels?
What stimulates cells to take in glucose lowering blood glucose levels?
Jan 1, 2019 · Akbari, Mohammad, and Chunara, Rumi. "Using Contextual Information to Improve Blood Glucose Prediction". Proceedings of Machine Learning ...
The broad objective of the work described in this paper is to investigate and improve blood glucose level prediction using recurrent neural networks.
In this paper, we describe a novel approach to the prediction of human blood glucose levels by analysing rich biometric human contextual data from a ...
We use continuous glucose monitoring and actigraphy data from 54 individuals with type 2 diabetes to predict their future hemoglobin A1c, HDL cholesterol, LDL ...
Feature-Based Machine Learning Model for Real-Time Hypoglycemia ...
pmc.ncbi.nlm.nih.gov › PMC8258517
Real-time data from continuous glucose monitoring (CGM) can be used to predict hypoglycemic risk, allowing patients to take timely intervention measures.