[HTML][HTML] Deep learning in mHealth for cardiovascular disease, diabetes, and cancer: systematic review
Background: Major chronic diseases such as cardiovascular disease (CVD), diabetes, and
cancer impose a significant burden on people and health care systems around the globe …
cancer impose a significant burden on people and health care systems around the globe …
The importance of interpreting machine learning models for blood glucose prediction in diabetes: an analysis using SHAP
Abstract Machine learning has become a popular tool for learning models of complex
dynamics from biomedical data. In Type 1 Diabetes (T1D) management, these models are …
dynamics from biomedical data. In Type 1 Diabetes (T1D) management, these models are …
[HTML][HTML] GARNN: an interpretable graph attentive recurrent neural network for predicting blood glucose levels via multivariate time series
Accurate prediction of future blood glucose (BG) levels can effectively improve BG
management for people living with type 1 or 2 diabetes, thereby reducing complications and …
management for people living with type 1 or 2 diabetes, thereby reducing complications and …
Artificial pancreas: A review of meal detection and carbohydrates counting techniques
E Rodriguez, R Villamizar - Review of Diabetic Studies, 2022 - ingentaconnect.com
OBJECTIVE: The development of an artificial pancreas is an open research problem that
faces the challenge of creating a control algorithm capable of dosing insulin automatically …
faces the challenge of creating a control algorithm capable of dosing insulin automatically …
Deep learning and regression approaches to forecasting blood glucose levels for type 1 diabetes
Objective: Controlling blood glucose in the euglycemic range is the main goal of develo**
the closed-loop insulin delivery system for type 1 diabetes patients. The closed-loop system …
the closed-loop insulin delivery system for type 1 diabetes patients. The closed-loop system …
Glugan: generating personalized glucose time series using generative adversarial networks
Time series data generated by continuous glucose monitoring sensors offer unparalleled
opportunities for develo** data-driven approaches, especially deep learning-based …
opportunities for develo** data-driven approaches, especially deep learning-based …
Exploring nutritional influence on blood glucose forecasting for Type 1 diabetes using explainable AI
Type 1 diabetes mellitus (T1DM) is characterized by insulin deficiency and blood sugar
control issues. The state-of-the-art solution is the artificial pancreas (AP), which integrates …
control issues. The state-of-the-art solution is the artificial pancreas (AP), which integrates …
[HTML][HTML] Model-free-communication federated learning: framework and application to precision medicine
The problem of executing machine learning algorithms over data while complying with data
privacy is highly relevant in many application areas, including medicine in general and …
privacy is highly relevant in many application areas, including medicine in general and …
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 …
[HTML][HTML] Hypoglycaemia prediction using information fusion and classifiers consensus
The recommendation that there must be a balance between insulin, food, and exercise to
keep diabetes under control provides an opportunity for develo** mobile applications for …
keep diabetes under control provides an opportunity for develo** mobile applications for …