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Article · Nazarbayev University Repository · April 20, 2026

Cardiology Diagnosis Automation Zhurek AI

Ablay Abdimalinov, Amina Aimuratova, Zhazelya Muratkhanova, Ariana Kenbayeva, Kymbat Amanova

Ablay Abdimalinov
Read on nur.nu.edu.kz

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.

Artificial Intelligence in Healthcare and EducationArtificial Intelligence in HealthcareCardiovascular Function and Risk Factorsechocardiographycardiovascular disease diagnosisexplainable AI

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