Using artificial intelligence to analyse and improve control and prevent complications of diabetes

This article addresses the integration of artificial intelligence into mobile applications for diabetes patients, which opens new possibilities for improving disease management, enhancing treatment effectiveness, and preventing complications. The use of artificial intelligence not only allows for blood glucose monitoring but also enables personalized therapy, risk prediction for diabetes and its complications. This contributes to improving patients’ quality of life and reducing the burden on healthcare systems by optimizing monitoring processes and automating treatment. The aim of the study is to analyze the significance of artificial intelligence in improving diabetes management and preventing its complications. The study employed general scientific methods, including critical analysis of scientific literature, data systematization, comparative analysis, and forecasting. These methods allowed for an examination of current approaches to the implementation of artificial intelligence in diabetes management and an evaluation of its effectiveness. The study results demonstrate that the use of artificial intelligence in mobile applications for diabetes patients helps to personalize treatment through the analysis of biological, social, and genetic data. This enables the prediction of diabetes risks, glucose level control, and automated insulin therapy. Additionally, artificial intelligence can detect complications, such as diabetic retinopathy and foot ulcers, which significantly improves diagnostics and facilitates remote health monitoring for patients. It has been confirmed that the implementation of artificial intelligence reduces the burden on healthcare systems and lowers patients’ financial expenses. However, certain challenges exist, including the technical complexity of developing such applications, the lack of data standardization, and low digital literacy among older patients, necessitating educational programs and government support. The application of artificial intelligence in apps for diabetes patients holds significant promise but requires overcoming technical and social barriers for full integration.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-10-15
DOI
https://doi.org/10.5281/zenodo.13949873
Primary Topic
Artificial Intelligence in Healthcare
Type
article
Field-Weighted Citation Impact
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article

Using artificial intelligence to analyse and improve control and prevent complications of diabetes

Zenodo (CERN European Organization for Nuclear Research)
Artificial Intelligence in Healthcare
article

Using artificial intelligence to analyse and improve control and prevent complications of diabetes

article en

Abstract

This article addresses the integration of artificial intelligence into mobile applications for diabetes patients, which opens new possibilities for improving disease management, enhancing treatment effectiveness, and preventing complications. The use of artificial intelligence not only allows for blood glucose monitoring but also enables personalized therapy, risk prediction for diabetes and its complications. This contributes to improving patients’ quality of life and reducing the burden on healthcare systems by optimizing monitoring processes and automating treatment. The aim of the study is to analyze the significance of artificial intelligence in improving diabetes management and preventing its complications. The study employed general scientific methods, including critical analysis of scientific literature, data systematization, comparative analysis, and forecasting. These methods allowed for an examination of current approaches to the implementation of artificial intelligence in diabetes management and an evaluation of its effectiveness. The study results demonstrate that the use of artificial intelligence in mobile applications for diabetes patients helps to personalize treatment through the analysis of biological, social, and genetic data. This enables the prediction of diabetes risks, glucose level control, and automated insulin therapy. Additionally, artificial intelligence can detect complications, such as diabetic retinopathy and foot ulcers, which significantly improves diagnostics and facilitates remote health monitoring for patients. It has been confirmed that the implementation of artificial intelligence reduces the burden on healthcare systems and lowers patients’ financial expenses. However, certain challenges exist, including the technical complexity of developing such applications, the lack of data standardization, and low digital literacy among older patients, necessitating educational programs and government support. The application of artificial intelligence in apps for diabetes patients holds significant promise but requires overcoming technical and social barriers for full integration.

Zenodo (CERN European Organization for Nuclear Research)
Elgin Community College (US)
Quality Education
Openalex Percentile: Top 48%
Artificial Intelligence in Healthcare
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