VUNO

VUNO Med System Architecture Assessment

As of January 2026, VUNO Med functions as a global medical AI orchestration layer, following its successful FDA clearance for cardiovascular and radiological suites. The architecture centers on the VUNO Med-DeepCARS™ and VUNO Med-DeepBrain® engines, which leverage a unified processing pipeline to analyze both pixel-based DICOM data and time-series physiological signals 📑. The system has moved to a Cloud-First SaaS model, utilizing AWS HealthImaging for low-latency delivery of neuro-quantification reports 📑.

Medical Imaging & Vital Sign Orchestration

The platform utilizes a modular, microservices-based architecture to manage high-concurrency diagnostic tasks.

• DeepCARS™ (Vital Signs): FDA-cleared engine that monitors BP, HR, RR, and BT via temporal transformers to predict in-hospital cardiac arrest (IHCA) up to 24 hours in advance 📑.
• DeepBrain® (SaaS MRI): Cloud-native brain parcellation engine that performs volumetric analysis of 100+ brain regions in <60 seconds, now featuring native RAG-based clinical summary generation 📑.
• Chest X-ray Triage: Automated prioritization of urgent findings (e.g., pneumothorax, pleural effusion) directly within the PACS worklist, optimized for 2026 clinical reimbursement standards 📑.

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Operational Scenarios

• Emergency Cardiac Prediction: Input: Vital sign telemetry (HR, RR, BP, BT) via HL7 FHIR R5 → Process: DeepCARS™ temporal analysis against 2.5M+ patient-hour baseline data → Output: Risk-score alert (0-100) integrated into the nurse's dashboard and mobile workstation 📑.
• Dementia Screening Workflow: Input: 3D T1-weighted brain MRI via DICOM STOW-RS to VUNO.CLOUD → Process: DeepBrain® automated atrophy quantification with AWS HealthImaging-accelerated reconstruction → Output: Volumetric report with percentile ranking and longitudinal comparison PDF 📑.

Evaluation Guidance

Technical evaluators should verify the following architectural characteristics:

• SaaS Latency (MRI): Benchmark the end-to-end turnaround time for 3D MRI quantification when using cloud-native reconstruction vs. legacy on-premise local nodes 🧠.
• FHIR R5 Ingest Pipeline: Organizations should validate the stability of bidirectional data flow between VUNO.CLOUD and specific EMR versions (Epic R5 / Cerner 2026) for real-time risk scores 🌑.
• Medical ASR Accuracy: Verify the error rate of VUNO Med-DeepASR® in specialized surgical environments where nomenclature differs from standard radiology dictation 🌑.