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dc.contributor.author | Kabdeshev, Adil | |
dc.date.accessioned | 2025-06-05T07:02:12Z | |
dc.date.available | 2025-06-05T07:02:12Z | |
dc.date.issued | 2025-04-16 | |
dc.identifier.isbn | 978-601-385-052-8 | |
dc.identifier.uri | http://repository.enu.kz/handle/enu/24037 | |
dc.description.abstract | The goal of this work is to develop a system that can diagnose and identify patients using AI and machine learning. Shortness of breath and cough are among the most common, urgent, and lifethreatening conditions in emergency departments. Cough holds critical information about many respiratory diseases and is a symptom of more than twenty different conditions. The hidden features within a cough can also be used for early disease detection by leveraging trained AI algorithms that analyze cough acoustic data. Approximately half of adults experiencing shortness of breath suffer from acute heart failure (AHF), exacerbation of chronic obstructive pulmonary disease (COPD), or pneumonia. These conditions are often misdiagnosed and, as a result, poorly treated in emergency care. Our goal is to develop AI-based diagnostic decision support with interpretable and individualized features, utilizing data collected from across the region. | ru |
dc.language.iso | en | ru |
dc.publisher | L.N. Gumilyov Eurasian National University | ru |
dc.subject | cough | ru |
dc.subject | artificial intelligence | ru |
dc.subject | shortness of breath | ru |
dc.subject | diagnosis | ru |
dc.subject | Covid-19 | ru |
dc.subject | diagnosis setting | ru |
dc.subject | analysis | ru |
dc.subject | AI in medicine | ru |
dc.subject | machine learning | ru |
dc.title | DEVELOPMENT OF AN INTELLIGENT HEALTH DIAGNOSIS SYSTEM BASED ON COUGH ANALYSIS | ru |
dc.type | Article | ru |