Miklos Nagy
1
,
Barbara Simon
1
,
László Szász
1
,
Máté Siket
1
,
Dénes-Fazakas Lehel
1
,
György Eigner
1
,
Patrik Péter Süli
1
,
Levente Kovács
1
,
László Szilágyi
1
1
University Research and Innovation Center, Physiological Controls Research Center, Óbuda University,Budapest,Hungary
|
Publication type: Proceedings Article
Publication date: 2024-05-23
Abstract
The summary provides an overview of the proliferation of diabetes management apps, highlighting their increasing availability and varied features. These apps allow users to log events related to insulin and carbohydrate intake, with some offering additional functionalities like tracking activity levels and stress. Logging capabilities range from basic timestamps to more complex entries with multiple attached data types. Integration of artificial intelligence enhances these apps, enabling predictive models for blood glucose levels and decision support. The summary introduces a web application for monitoring and managing diabetes patients, emphasizing its predictive blood glucose feature based on patient parameters. It includes detailed explanations of module usage and discusses potential future developments, stressing the importance of secure medical data management.
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