AN INTERDISCIPLINARY APPROACH TO PNEUMOCONIOSIS DIAGNOSIS USING ARTIFICIAL INTELLIGENCE: INTEGRATION OF MORPHOLOGY, CYTOLOGY, AND CLINICAL PRACTICE, A STRATEGY FOR PRESERVING THE HEALTH OF MINERS IN KEMEROVO REGION
Main Article Content
Abstract
Objective – to justify the necessity of implementing artificial intelligence (AI) into the diagnostic system for pneumoconiosis among coal industry workers in the Kemerovo Region (Kuzbass).
Materials and methods. The study included cytological specimens of sputum and bronchoalveolar lavage from 60 miners, as well as histological lung tissue samples from 18 patients with verified pneumoconiosis. Manual, morphometric, and AI-based analyses were compared, with the latter utilizing a convolutional neural network trained on a verified archive of specimens developed by the research team of the Novokuznetsk Institute for Occupational Health and Diseases (NGIUV).
Results. AI reduced histological slide analysis time from 25 ± 6 minutes to 7 ± 1 minutes, decreased the coefficient of variation from 18-22% to 2-3%, and increased sensitivity for detecting coal-dust-related lesions smaller than 0.5 mm² to 94%. Objective AI-derived quantitative parameters were established: Dust Accumulation Index (DAI), Histological Fibrosis Index (HFI), and Epithelial Degeneration Coefficient (EDC). These parameters demonstrated significant correlations with FEV₁ (r = –0.71 to –0.79; p < 0.001).
Conclusion. AI ensures objectivity, reproducibility, and early diagnosis of pneumoconiosis – particularly critical given the shortage of occupational pathology specialists in Kuzbass. Integrating AI into both clinical practice and the educational curriculum at NGIUV fosters a sustainable «science – education – practice» cycle. This study confirms the feasibility and urgency of digital transformation in occupational pathology and morphological diagnostics in the region.
Keywords
Author Biographies
Oleg Ivanovich Bondarev,
Oleg I. Bondarev
MD, PhD, head of the research laboratory for pathological anatomy
Sergey Nikolaevich Filimonov,
doctor of medical sciences, professor, head of the department of human ecology, public health and healthcare; professor of the therapy departmentTatyana Valeryevna Kalashnikova,
candidate of medical sciences, docent of the department of psychiatry, psychotherapy, and narcologyArticle Details
Information about financing and conflict of interests
The authors declare that they have no apparent or potential conflicts of interest related to the publication of this article.
This work is licensed under a Creative Commons Attribution 4.0 License.
How to Cite
References
Ostanina AA. Zabolevaemost na promishlennikh predpriyatiyakh Kuzbassa: analiz i puti snizheniya. Materiali Vseros. 70 nauch.-prakt. konf. molodikh uchenikh «Rossiya molodaya». 22-25 aprelya 2025 g. Kemerovo, 2025. S. 1-6. Russian (Останина А.А. Заболеваемость на промышленных предприятиях Кузбасса: анализ и пути снижения //Материалы Всерос. 70 науч.-практ. конф. молодых ученых «Россия молодая». 22-25 апреля 2025 г. Кемерово, 2025. С. 1-6)
Bondarev OI, Filimonov SN. Digitalization of diagnosis and prevention of pneumoconiosis among kuzbass miners: integration of telemedicine and big data analytics for coal industry workers’ health protection. Medicine in Kuzbass. 2025; 24(2): 10-15. Russian (Бондарев О.И., Филимонов С.Н. Цифровизация диагностики и профилактики пылевых поражений легких у шахтеров Кузбасса: интеграция телемедицины и аналитики больших данных для защиты здоровья работников угольной отрасли //Медицина в Кузбассе. 2025. Т. 24, № 2. С. 10-15.) doi: 10.24412/2687-0053-2025-2-10-15
Bondarev OI. Database of Autopsy Materials from Kuzbass Miners (2010-2018). Russian Federal Service for Intellectual Property Registration Certificate N 2019620436; Application N 2019620268, filed February 28, 2019. Russian (Бондарев О.И. База данных аутопсийного материала по шахтерам Кузбасса за 2010-2018 гг. //Свидетельство о регистрации в государственной федеральной службе по интеллектуальной собственности за номером № 2019620436, заявка № 2019620268 от 28 февраля 2019 года)
Proceedings of the All-Russian Scientific and Practical Conference with International Participation «Healthy Environment». Ed. by AYu Popova, AB Bakirov. Ufa, 2024. 297 p. Russian (Матер. Всерос. науч.-практ. конф. с междунар. участием «Здоровая среда» //под ред. А.Ю. Поповой, А.Б. Бакирова. Уфа, 2024. 297 с.)
Current Issues in Public Health Surveillance in Siberia: proceedings of the ii interregiona. scient.-pract. conf. dedicated to the 60th anniversary of the faculty of medical prevention, Kemerovo State Medical University (Kemerovo, April 5, 2024). Kemerovo: KemSMU, 2024. 90 p. Russian (Актуальные вопросы госсанэпиднадзора в Сибири: матер. II Межрегион. науч.-практ. конф., посвящ. 60-летию мед.-проф. факультета Кем ГМУ: сборник трудов (г. Кемерово, 5 апреля 2024 г.). Кемерово: КемГМУ, 2024. 90 с.)
Institute for Statistical Studies and Economics of Knowledge, National Research University Higher School of Economics (HSE). Artificial Intelligence Technologies in Russian Business: 2024. M.: HSE Publishing House, 2025. Russian (Институт статистических исследований и экономики знаний НИУ ВШЭ. Технологии искусственного интеллекта в российском бизнесе: 2024. М.: ВШЭ, 2025)
VII International Scientific Forum «Step into the Future: Global Foresight, Artificial Intelligence, and Strategic Leadership»: collection of scientific papers in 2 volumes. Ed. by PV. Terelyansky. M.: Russian State University of Economics (REU) named after G.V. Plekhanov, 2025. 256 p. Russian (VII Международный научный форум «Шаг в будущее: глобальный форсайт, искусственный интеллект и стратегическое лидерство»: сб. науч. статей: в 2 т. /под ред. П.В. Терелянского. М.: ФГБОУ ВО «РЭУ им. Г. В. Плеханова», 2025. 256 с.)