ЦИФРОВИЗАЦИЯ ДИАГНОСТИКИ И ПРОФИЛАКТИКИ ПЫЛЕВЫХ ПОРАЖЕНИЙ ЛЕГКИХ У ШАХТЕРОВ КУЗБАССА: ИНТЕГРАЦИЯ ТЕЛЕМЕДИЦИНЫ И АНАЛИТИКИ БОЛЬШИХ ДАННЫХ ДЛЯ ЗАЩИТЫ ЗДОРОВЬЯ РАБОТНИКОВ УГОЛЬНОЙ ОТРАСЛИ

Abstract

The implementation of digital technologies significantly improves the diagnosis, monitoring, and prevention of occupational diseases caused by chronic inhalation of coal dust in the coal industry. This paper presents the results of a study on cytological criteria that enable the identification of pulmonary dust lesions at various stages of their development. The use of modern digital platforms (telemedicine, big data, image analysis) and specialized software, such as the automated counting program «BioVision 4 series», is examined as contributing to more accurate and faster diagnostics, as well as improving the effectiveness of preventive measures. These results can be integrated into a digital medical examination support system, which significantly contributes to the modernization of occupational safety approaches and the innovative development of the coal industry.
Aim of the study is to evaluate the effectiveness of the «BioVision 4 series» program for diagnosing pneumoconiosis, as well as to conduct a comparative analysis of automated and traditional methods for diagnosing fibrotic changes and dust inclusions in lung tissue.
Materials and methods. The study involved cytological samples from 100 coal industry workers diagnosed with pneumoconiosis. The samples were processed using both traditional manual methods and the «BioVision 4 series» program. The main parameters for analysis were the area of fibrotic changes, the number of dust inclusions, and the level of inflammation in the lung tissue. All data were subjected to statistical processing to identify relationships between age, disease stage, and analysis results.
Results. The results of the study demonstrated that the automated method using the «BioVision 4 series» software significantly increases diagnostic accuracy, reducing both analysis time and the number of errors in counting cells and dust inclusions. It was also found that in the later stages of the disease, there is a marked increase in the area of fibrotic changes and the number of dust inclusions. The analysis of the obtained data indicates the high efficiency of the developed program in monitoring disease dynamics and facilitating early diagnosis. Additionally, the software enables the creation of a structured database with photo documentation, allows for the preservation and continuous updating of information during follow-up, and generates comparative reports. These features contribute to enhancing the informativeness of clinical assessments and support evidence-based diagnostic decision-making.
Conclusions. The use of the «BioVision 4 series» program for diagnosing pneumoconiosis is a highly effective tool that provides more accurate and faster results compared to traditional methods. This opens new possibilities for early diagnosis, monitoring the health status of coal industry workers, and improving medical services in this field.