International Journal of Electrical and Computer Engineering (IJECE) Vol. 13, No. 6, December 2023, pp. 6778~6786 ISSN: 2088-8708, DOI: 10.11591/ijece.v13i6.pp6778-6786  6778 Journal homepage: http://ijece.iaescore.com Detection of lung pathology using the fractal method Gulzira Abdikerimova 1 , Ainur Shekerbek 1 , Murat Tulenbayev 2 , Bakhyt Sultanova 3 , Svetlana Beglerova 2 , Elvira Dzhaulybaeva 4 , Kamshat Zhumakanova 5 , Bakhytgul Rysbekkyzy 6 1 Department of Information Systems, Faculty of Information Technology, L.N. Gumilyov Eurasian National University, Astana, Republic of Kazakhstan 2 Department of Information Systems, Faculty of Information Technology, M.Kh. Dulaty Taraz Regional University, Taraz, Republic of Kazakhstan 3 Department of Information and Computing Systems, Faculty of Innovative Technologies, Karaganda, Technical University named after A. Saginov, Karaganda, Republic of Kazakhstan 4 Department of Biostatistics, Bioinformatics and Information Technologies, Astana Medical University, Astana, Republic of Kazakhstan 5 Department of Biostatistics, Pediatrics and Neonatology, Karaganda Medical University, Karaganda, Republic of Kazakhstan 6 Department of Information Technology and Security, Innovative Technologies, Karaganda Technical University named after A. Saginov, Karaganda, Republic of Kazakhstan Article Info ABSTRACT Article history: Received Jun 21, 2023 Revised Jul 7, 2023 Accepted Jul 9, 2023 Currently, the detection of pathology of lung cavities and their digitalization is one of the urgent problems of the healthcare industry in Kazakhstan. In this paper, the method of fractal analysis was considered to solve the task set. Diagnosis of lung pathology based on fractal analysis is an actively developing area of medical research. Conducted experiments on a set of clinical data confirm the effectiveness of the proposed methodology. The results obtained show that fractal analysis can be a useful tool for early detection of lung pathologies. It allows you to detect even minor changes in the structure and texture of lung tissues, which may not be obvious during visual analysis. The article deals with images of pathology of the pulmonary cavity, taken from an open data source. Based on the analysis of fractal objects, they were pre-assembled. Software algorithms for the operation of the information system for screening diagnostics have been developed. Based on the information contained in the fractal image of the lungs, mathematical models have been developed to create a diagnostic rule. A reference set of information features has been created that allows you to create algorithms for diagnosing the lungs: healthy and with pathologies of tuberculosis. Keywords: Chest radiograph Digitalization Fractal analysis Fractal dimension Medical imaging texture Pathology This is an open access article under the CC BY-SA license. Corresponding Author: Ainur Shekerbek Department of Information Systems, Faculty of Information Technology, L.N. Gumilyov Eurasian National University 010000 Astana, Republic of Kazakhstan Email: shekerbek80@mail.ru 1. INTRODUCTION According to official data, the number of patients with pneumonia is registered annually in Kazakhstan, for example, in 2020 to 3,000, in 2021 to 4,000, and in 2022 to 5,000. At the moment, there is a high probability of damage to respiratory diseases. For the timely detection of the most severe of them, each person must undergo an annual fluorography. At this stage, there is a possibility of an error-an unnoticed pathology will remain with a person for a year, turning into a more serious form and having complications. Provided that the specialist has discovered the pathology, the patient needs to undergo an x-ray, which will only increase the likelihood of a diagnosis. Therefore, the detection of pathologies on radiographs today is an urgent problem. To reduce the error in annual fluorography, as well as speed up the