Nishagee Jeewantha@nishagii

CardioCore is a distributed agentic cardiac assessment system running across two AMD Instinct MI300X GPU nodes. Instance B hosts a FastAPI MCP server exposing five clinical tools, alongside a specialist inference server running PULSE-7B — a 7B multimodal LLM fine-tuned on ECG data — loaded directly into GPU memory. Instance A runs Gemma 3 27B via vLLM, acting as the vision-language reasoning engine for echocardiographic analysis. When a clinician uploads an ECG image, PULSE-7B classifies the cardiac rhythm into one of five SNOMED-CT categories: normal sinus rhythm, myocardial infarction, ST-T wave change, conduction disorder, or hypertrophy. For echocardiogram video, two frames are extracted and sent to Gemma 3, which estimates left ventricular ejection fraction, classifies heart failure severity, and identifies structural abnormalities. HEART score risk stratification runs in pure Python under 1ms, combining ECG results, echo findings, patient age, troponin ratio, and comorbidities into a validated 10-point triage score predicting 10-day major adverse cardiac events. Finally, all results are assembled into a schema-validated HL7 FHIR R4 Bundle containing a DiagnosticReport and two LOINC-coded Observations, ready for EHR submission. The browser UI orchestrates the entire pipeline — each tool passes its result directly into the next, with no separate pipeline infrastructure required beyond the two running FastAPI servers.

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