Automated diabetes detection prediction system based on patients’ medical data
The development of an automated system for predicting diabetes detection is an extremely relevant task, especially given the rapid increase in the number of diabetes cases in Ukraine and worldwide. The issue has become particularly burning in Ukraine due to military actions, which have deteriorated...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Zhytomyr Polytechnic State University
2025-07-01
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| Series: | Технічна інженерія |
| Subjects: | |
| Online Access: | https://ten.ztu.edu.ua/article/view/334773 |
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| Summary: | The development of an automated system for predicting diabetes detection is an extremely relevant task, especially given the rapid increase in the number of diabetes cases in Ukraine and worldwide. The issue has become particularly burning in Ukraine due to military actions, which have deteriorated the overall health condition of the population, increased stress levels, and disrupted the normal way of life. Type 2 diabetes, which accounts for the majority of diabetes cases, often remains unnoticed in the early stages, significantly complicating subsequent treatment and leading to severe complications such as cardiovascular diseases, blindness, limb amputations, and kidney failure. Early and accurate diagnosis allows effective disease management, significantly improves patients' quality of life, and reduces the financial burden on the healthcare system. Given the continuous growth of medical data volumes, there is a clear need for modern information technologies capable of automating disease analysis and prediction processes. This paper examines the potential and benefits of implementing machine learning (ML) and artificial intelligence (AI) algorithms for medical data analysis aimed at diabetes detection. It has been proven that the application of such technologies significantly enhances the accuracy of disease prediction and diagnosis, enabling timely identification of at-risk patients and providing necessary medical care at early stages. Furthermore, these systems create new opportunities for developers to monetize solutions, improving the economic efficiency of medical institutions by optimizing treatment costs. The proposed approach demonstrates substantial potential for integration into modern medical practice, making it an essential tool for further improving the healthcare sector. It contributes to the strategic objectives of medicine digitalization, the development of preventive strategies, and the enhancement of overall public health levels in Ukraine and other countries. |
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| ISSN: | 2706-5847 2707-9619 |