Overburdened Staff and Delayed Examinations
Inconsistent Measurements
from the Same Image
With a critical shortage of skilled specialists, measurement values frequently vary depending on the examiner. There is an urgent need for standardized support to ensure high reproducibility and consistency.
Prolonged Examination Times
Manually measuring dozens of cardiac parameters and compiling comprehensive reports significantly slows down the daily clinical workflow.
The Need for Clear,
Detailed Insights
Accurate and easily digestible test results are essential to facilitate swift follow-up testing and support confident, timely clinical decision-making.
Exceptional Outcomes,
Simplified Experience
SONIX HEALTH accelerates the adoption of AI in cardiology. Driven by deep expertise in both medicine and artificial intelligence, we deliver solutions optimized for the clinical frontline.
Flexible Compatibility
Supports major multi-vendor and multi-device environments, significantly reducing the financial and operational burden of equipment replacement.
Versatile Deployment
Available in both cloud and on-premise configurations, allowing seamless deployment tailored to your hospital’s specific security policies and IT infrastructure.
Automated Cardiac Cycle Detection
AI intelligently detects the cardiac cycle to drastically streamline the measurement workflow.
SoniX : The AI Echocardiography OS
Supporting the entire echocardiography workflow
from image acquisition and automated analysis to comprehensive reporting.
Empowering Everyone at the Clinical Frontline
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Hospital Administrators Facing Staffing Shortages
Streamline examination workflows without adding headcount, effectively reducing operational and labor cost burdens.
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Institutions Lacking Skilled Clinicians
Ensure standardized image acquisition and highly consistent measurements through real-time AI scan guidance and automated analysis.
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Executives of Large-Scale Health Screening Centers
Eliminate operational bottlenecks and lower overhead costs with a seamless, end-to-end flow from scan to final report.
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Hospital IT Managers
Minimize the burden of system integration through robust multi-vendor compatibility and flexible deployment options (Cloud/On-Premise).
Clinical and technological research underpins
the performance of our solutions
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- Artificial Intelligence-Enhanced Analysis of Echocardiography-Based Radiomic Features for Myocardial Hypertrophy Detection and Etiology Differentiation
- Inki Moon, Jina Lee, Seung-Ah Lee, Dawun Jeong, Jaeik Jeon, Yeonggul Jang, Sihyeon Jeong, Jiyeon Kim, Hong-Mi Choi, In-Chang Hwang, Youngtaek Hong, Goo-Yeong Cho, Yeonyee E Yoon, Hyuk-Jae Chang
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- Predicting categories of coronary artery calcium scores from chest X-ray images using deep learning
- Youngtaek Hong, Hyunseok Jeong, Younggul Jang, Ran Heo, Seung-Ah Lee, Yeonyee E Yoon, Jina Lee, Hyung-Bok Park, Hyuk-Jae Chang
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- Deep Learning-Based Detection and Severity Assessment of Bicuspid Aortic Valve Stenosis
- Jiesuck Park, Jiyeon Kim, Jaeik Jeon, Yeonyee E Yoon, Yeonggul Jang, Hyunseok Jeong, Seung-Ah Lee, Hong-Mi Choi, In-Chang Hwang, Goo-Yeong Cho, Hyuk-Jae Chang
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- Utilizing deep learning for accurate assessment of aortic valve stenosis: case series for clinical applications
- Jiesuck Park, Jiyeon Kim, Jaeik Jeon, Yeonyee E Yoon
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