Abstract
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 of these challenges may be addressed by means of computerised systems which may pave the way to provide practitioners with insight on their patient’s conditions anywhere and at anytime, but also to empower Diabetes patients as managers of their health. These systems for disease management come in many shapes and sizes, being the most promising trends the ones that involve expert systems that comprise specialised knowledge, use predictive models, feature engineering and reasoning. This study presents the state-of-the-art on reasoning and prediction models related with either blood glucose level or hypoglycaemia events. The main findings revealed are that there is room for improvement on predictive models, namely to enhance its accuracy and ability to forecast future events into a wider time frame. On the other hand, reasoning models are understudied and its usage in Diabetes management is reduced. We discuss an architecture that combines a predictive model and a reasoning system, with the objective of alerting of impending occurrences and interpret the current situation to accurately advise the diabetic user.
Highlights
D IABETES is a chronic disease that in 2019 affected approximately 463 million adults around the world (International Diabetes Federation, 2019)
This study aims to provide an up-to-date state-of-the-art on data-based or hybrid models applied to predict either blood glucose levels or hypoglycaemia events by means of data collected from patients with diabetes
In this article we reviewed the work being done for glycaemia prediction and for reasoning in diabetes management for patients
Summary
D IABETES is a chronic disease that in 2019 affected approximately 463 million adults around the world (International Diabetes Federation, 2019). Despite all the efforts to stale the growth of this disease, the number of people with diabetes is continuously increasing and it is estimated to reach 700 million in 2045 (International Diabetes Federation, 2019). Given the diabetic’s inability to produce insulin, a strict regime and periodic or even continuous verification of glycaemic values is recommended. This regime evolves and adapts each time the diabetic consults a doctor. In these appointments, the medical expert evaluates the evolution of the glycaemic values, among other relevant annotated information, and personalises the current regime, to the diabetic’s needs. Real-time events such as hyperglycaemia (when concentration of Blood Glucose (BG) is high) or hypoglycaemia (when BG is low), require immediate action which poses a possible problem in the absence of expert knowledge
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
