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dc.contributor.author | Atagulov, Ardak![]() |
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dc.contributor.author | Kakimbekov, Daniyar![]() |
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dc.contributor.author | Malikov, Nurbek![]() |
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dc.contributor.author | Moldabayev, Madiyar![]() |
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dc.date.accessioned | 2024-06-13T07:08:44Z | |
dc.date.available | 2024-06-13T07:08:44Z | |
dc.date.issued | 2024-05-04 | |
dc.identifier.citation | Atagulov, A. Kakimbekov, D. Malikov, N. Moldabayev, M. (2024). HeartUp: Diagnosing and monitoring heart failure with multi-modal data. Nazarbayev University School of Engineering and Digital Sciences. | en_US |
dc.identifier.uri | http://nur.nu.edu.kz/handle/123456789/7846 | |
dc.description.abstract | This paper presents HeartUp, an innovative cardiology management system designed to enhance the diagnosis and monitoring of heart failure (HF) conditions, which currently affect 26 million patients worldwide. Heart failure management is often hindered by delayed treatment and insufficient monitoring despite the availability of extensive patient data, leading to severe and sometimes fatal outcomes. HeartUp addresses these challenges by integrating and processing various forms of essential cardiac diagnostic data, including medical forms, heart sound recordings, and electrocardiograms (ECG). The system also evaluates the feasibility of using left ventricular assisting devices (LVADs) for individual patients. LVADs, although beneficial for regulating blood flow, are hampered by high manufacturing and maintenance costs, making their widespread use problematic. HeartUp’s comprehensive management solution leverages multimodal data inputs—such as audio, echocardiography, imaging, and laboratory analyses—to provide cardiologists with a robust tool for assessing patient conditions and making informed decisions regarding the viability of LVAD deployment. By streamlining the storage, processing, and reporting of cardiac health data, HeartUp aims to improve the quality of care and patient outcomes in cardiology by facilitating timely and accurate treatment interventions. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Nazarbayev University School of Engineering and Digital Sciences | en_US |
dc.rights | Attribution-NonCommercial 3.0 United States | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc/3.0/us/ | * |
dc.subject | Type of access: Open Access | en_US |
dc.subject | Deep Learning | en_US |
dc.subject | Healthcare Data Science | en_US |
dc.subject | ECG | en_US |
dc.subject | EchoNet Dynamic | en_US |
dc.subject | Echocardiography | en_US |
dc.title | HEARTUP: DIAGNOSING AND MONITORING HEART FAILURE WITH MULTI-MODAL DATA | en_US |
dc.type | Bachelor's thesis | en_US |
workflow.import.source | science |
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