Development of a Medical Decision Support System for Lung Disease Diagnosis Using Deep Learning

dc.contributor.authorMedeuova Zh.
dc.date.accessioned2026-04-07T10:45:19Z
dc.date.available2026-04-07T10:45:19Z
dc.date.issued2025
dc.description.abstractLung diseases such as Chronic Obstructive Pulmonary Disease (COPD), asthma, and pneumonia remain a leading cause of morbidity and mortality worldwide, with developing countries like Kazakhstan experiencing a rising burden due to environmental and lifestyle factors. Traditional diagnostic methods, while effective, are often limited by cost, accessibility, and dependence on expert interpretation, especially in low-resource settings. To address these challenges, this study proposes a novel artificial intelligence DL based decision support system that classifies lung conditions into three categories like normal, COPD. Using multimodal data: chest X-rays and lung sound recordings. The system utilizes a dual-stream deep learning architecture with late fusion to extract and integrate features from each modality independently, removing the need for synthetically paired datasets. This approach not only improves diagnostic scalability and accuracy but also provides a practical, low-cost solution for early lung disease detection, particularly in underserved regions. The model’s performance demonstrates the viability of using real-world, unpaired data for multimodal diagnostics, offering a significant step toward accessible, AI-driven respiratory healthcare
dc.identifier.citationMedeuova Zh / Development of a Medical Decision Support System for Lung Disease Diagnosis Using Deep Learning / SDU University / Faculty of Engineering and Natural Sciences
dc.identifier.urihttps://repository.sdu.edu.kz/handle/123456789/2583
dc.language.isoen
dc.publisherSDU University
dc.subjectCOPD
dc.subjectLung diseases
dc.subjectAI-driven respiratory healthcare
dc.titleDevelopment of a Medical Decision Support System for Lung Disease Diagnosis Using Deep Learning
dc.typeThesis

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