Cardiology Diagnosis Automation Zhurek AI
Loading...
Date
Journal Title
Journal ISSN
Volume Title
Publisher
Nazarbayev University School of Engineering and Digital Sciences
Abstract
The 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.
Description
Keywords
Citation
Abdimalinov, 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 Cardiology diagnosis automation: Zhurek AI [Unpublished senior project].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
Collections
Endorsement
Review
Supplemented By
Referenced By
Creative Commons license
Except where otherwised noted, this item's license is described as Attribution-NonCommercial-NoDerivs 3.0 United States
