Lead II
25 mm/s
10 mm/mV
Sinus rhythm
72 bpm
PR 164 ms
QRS 88 ms
QTc 418 ms
Filtered

Cardio
Suite

For research use only

Seven modules · One integrated workflow

01 / mqDiagnostic

mqDiagnostic

Cardiovascular analysis combining deterministic rule-based detection with neural-network classification — delivering ECG and echocardiography analysis with transparent, explainable reasoning that researchers and professionals can inspect and validate.

  • 01Hybrid inferenceRule-based detection combined with neural-network classification for ECG and echocardiography
  • 02ExplainableHuman-readable decision reasoning with 3D heart model viewing
  • 03Real-timeSub-second analysis output
  • 04ReviewedBuilt with cardiologist input and domain expert review
Coronary Artery Disease
LIVE
ECGQRS
RhythmSinus
QRS104 ms
STDepression
97%
Echo
EF44%
LVHypokinesia
MVCompetent
94%
BiomarkersTnIBNPCRPD-DHbA1CholLDLHDL
Troponin I1.24 ng/mL
BNP310 pg/mL
Vitals
HR96 bpm
BP158/94
SpO₂95%
Temp37.4 °C
02 / mqTherapy

mqTherapy

Guideline-based therapy models generated by combining cardiovascular domain rules with language-model reasoning — derived from a research subject's profile: analysis results, biomarkers, vitals, and echocardiography. Each model covers medication, nutrition, and exercise as a structured FHIR R4 Bundle for researcher review and system integration.

  • 01OutputTherapy plans delivered as structured FHIR R4 Bundles covering medication, nutrition, and exercise
  • 02PersonalisedAdapts to patient comorbidities, renal function, EF, and contraindications
  • 03Guideline-basedGrounded in current ESC / ACC / AHA recommendations
  • 04HolisticIntegrated medication, nutrition, and exercise recommendations in one plan
CAD · NSTEMI
FHIR
Medication
Aspirin100 mg · 1×/day
Ticagrelor90 mg · 2×/day
Bisoprolol5 mg · 1×/day
Ramipril5 mg · 1×/day
Atorvastatin80 mg · nocte
Nutrition
1 800 kcal · low sodiumMed diet
Exercise
Walking30 min · 3×/wk · RPE 11
Cycling20 min · 2×/wk · RPE 12
03 / mqData

mqData

Secure, sovereign data storage. Retain patient records, biosignals, and diagnostic outputs with configurable retention periods, storage capacity, and data residency region — built for regulatory compliance from day one.

  • 01SecureEnd-to-end encryption for medical data at rest and in transit, compliant with GDPR
  • 02RetentionConfigurable data retention periods per organization policy and jurisdictional requirements
  • 03CapacityScalable storage with configurable per-organization limits and usage monitoring
  • 04RegionData residency selection to ensure compliance with local healthcare data regulations
Data Store
SECURE
Capacity42 GB / 100 GB
Configuration
Retention365 days
RegionEU · Frankfurt
EncryptionAES-256
Records
Patients1 204
ECG signals8 731
Reports3 490
04 / mqPrompt

mqPrompt

A language-model assistant embedded directly in the mQ-up suite, grounded in the platform's domain rules and structured data. Ask about ECG findings, therapy models, research workflows, or cardiovascular physiology — in plain language.

  • 01ContextualKnows the mQ-up research context — reports, workflows, biosignal types
  • 02Multi-providerOpenAI-compatible endpoints, Groq, Anthropic, Google — free tier available on select providers
  • 03ConfigurablePer-organization AI model Hub — set provider and model in Admin
  • 04PrivateRuns server-side; no conversation data leaves your configured provider

mqPrompt

Cardiovascular informatics · rules + AI

Summarize the ECG findings for subject A-2847.
Subject A-2847 shows sinus rhythm at 72 bpm with ST depression in V4–V6 (−1.2 mV) and a prolonged QTc of 468 ms. Two prior fusions for comparison are available in the data panel.
research output · not for clinical use
Which ESC guidelines are relevant here?
Ask about a research subject…
05 / mqConsult

mqConsult

A guided research workflow tool combining structured cardiovascular domain rules with language-model reasoning — carrying research subjects from data intake to therapy modelling, step by step.

  • 01GuidedStep-by-step research workflow from data intake to therapy modelling
  • 02Rules + modelDeterministic cardiovascular domain rules validated and extended by AI-assisted reasoning
  • 03AdaptiveAdjusts depth and language for medical professionals or individual patients
  • 04IntegratedWorks with patient records, encounter data, and analysis results in the suite

mqConsult

medProfindividual

Guided research workflow

Intake
Analysis
Planning
Output

STEP 2 / 4 — ANALYSIS IN PROGRESS

06 / mqGenerator

mqGenerator

Synthetic medical data generation for research, training, and system validation. Produce physiologically accurate ECG signals, echocardiography studies, and patient-specific 3D heart models at scale — without compromising patient privacy.

  • 01SynthesisPhysiologically accurate ECG, echocardiography, biomarkers, vitals, and 3D heart model generation
  • 02ParametricConfigurable patient and condition profiles
  • 03ScaleBatch generation for training datasets
  • 04StandardsHL7, FHIR, and DICOM-compatible output
Generator Output
GEN
ECG
✓
Echo
✓
Biomarker · Vital · Profile
✓
07 / mqHub

mqHub

The integration layer that connects the entire suite. mqHub bridges cloud storage, databases, local filesystems, and LLM/SLM APIs — so every module can ingest data, route outputs, and integrate with existing eHealth ecosystems without custom connectors.

  • 01Cloud & localS3-compatible storage, web databases, and local filesystem roots — all as named hubs
  • 02LLM / SLM APIsRoute research prompts to any OpenAI-compatible endpoint, Groq, Anthropic, or Google
  • 03In · Out · InOutEach hub is configured for ingestion, distribution, or bidirectional data exchange
  • 04FHIR & HL7Output hubs serve FHIR R4 Bundles and HL7 v2 — no custom connectors required
Hub Registry
ACTIVE
cloud storageCloud storage · biodata-eu
in
web databaseWeb database · records-db
inout
local filesystem/data/org-001
in
llm apiAI model API · configured
out
CardioFusion integration diagram
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