Cardiology Diagnosis Automation Zhurek AI

dc.contributor.advisorFazli, Siamac
dc.contributor.advisorAbilgazym, Aibek
dc.contributor.authorAbdimalinov, Ablay
dc.contributor.authorAimuratova, Amina
dc.contributor.authorMuratkhanova, Zhazelya
dc.contributor.authorKenbayeva, Ariana
dc.contributor.authorAmanova, Kymbat
dc.date.accessioned2026-06-09T05:38:16Z
dc.date.issued2026-04-20
dc.description.abstractThe leading cause of deaths in Kazakhstan is Cardiovascular disease(CDV). Some revisions were made in international heart-failure guidelines since 2016, but new diagnostic standards are adopted slowly in primary care, especially outside main cities [1]. This gap is caused by a noticeable shortage of specialists capable of interpreting echocardiographic (echo) studies. Based on this, the team identified three key objectives: 1. Lessen the reliance on specialists by automating echocardiographic analysis. 2. Lower the amount of misinterpretation of important cardiac measurements through AI-driven report generation. 3. Ensure clinical transparency through explainable and verifiable AI outputs that clinicians can trust. To address these objectives the team built Zhurek AI, an AI-powered web platform for echocardiography analysis. The platform creates structured clinical reports covering ejection fraction, valvular evaluation, wall motion, and pericardial findings. It is powered by EchoPrime [2], a multi-video view-informed vision-language model trained on 12.1 million echocardiographic clips, which achieves a mean AUC of 0.85–0.92 and exceeds human cardiologists on several tasks.
dc.identifier.citationAbdimalinov, A., Aimuratova, A., Muratkhanova, Z., Kenbayeva, & A., Amanova, K.(2026). Cardiology diagnosis automation: Zhurek AI [Unpublished senior project]. Nazarbayev University School of Engineering and Digital Sciences
dc.identifier.urihttps://nur.nu.edu.kz/handle/123456789/18905
dc.language.isoen_US
dc.publisherNazarbayev University School of Engineering and Digital Sciences
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 United Statesen
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/us/
dc.subjectCardiovascular Disease
dc.subjectAI
dc.subjectGrad-CAM
dc.titleCardiology Diagnosis Automation Zhurek AI
dc.typeBachelor's Capstone project

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