AI service — AI Medical · Cardiology
Echocardiography analysis
Measure ejection fraction, wall thickness and chamber function from echocardiogram video, and retrieve comparable studies by description.
Send us your data volume, throughput and latency targets and any constraint we should design around. You get a proposed configuration, a benchmark on your own data, and a known cost per unit of work before you commit.
An echo study is video, and the measurements that matter — ejection fraction, wall thickness, chamber volumes — are read off it by hand today. These models return those numbers directly from the loop, with the segmentation that produced them attached, so a cardiologist checks a measurement instead of taking one.
Studies arrive from your PACS, a DICOM store or a watched folder and come back as measurements, masks and study-level findings. The newer vision-language models also index a study archive so it can be searched by description rather than by report text.
Every output is clinical decision support, not a diagnosis: a qualified professional reviews and signs it. Where clinical use requires regulatory approval in your jurisdiction, that approval remains yours to hold — we provide the infrastructure, the model operations and the audit trail behind it.
What we size for
We build the echocardiography analysis pipeline around the workload you actually have: data format, accuracy target, latency, throughput, concurrency, retention and scheduling. Start with a pilot, then scale production capacity without changing a line of your integration.
Common use cases
- Ejection fraction at volume — Measure EF consistently across every study rather than in a sampled few.
- Screening from existing archives — Re-read recorded studies for amyloidosis, hypertrophy or low EF.
- Comparable-case retrieval — Find previously reported studies that resemble the one on screen.
More Cardiology services
- ECG interpretationECG interpretation service →
- Cardiac MRI analysisCardiac MRI analysis service →