← Back to Data Room

CARDIO AI

Product Overview & Technology Documentation

Unified Master Orchestrator with 3 Integrated Subsystems

Platform Architecture Overview

Cardio AI is built on a sophisticated Unified Master Orchestrator architecture that coordinates three specialized subsystems to deliver comprehensive cardiovascular care. The platform integrates real-time device monitoring, advanced AI diagnostics, medical imaging analysis, and validated risk prediction into a seamless clinical workflow that processes patient data from initial vital signs through final treatment recommendations.

Master Orchestrator: Central Coordination Engine

The Master Orchestrator serves as the central intelligence hub managing all subsystems with real-time task routing, load balancing, and state management. This sophisticated coordination layer ensures optimal resource utilization, automatic error recovery, and comprehensive performance monitoring across the entire platform.

Core Orchestrator Functions

Task Routing

Intelligent routing of clinical tasks across all subsystems based on task type, priority, and system capacity:

• Queue Management: Prioritized task queues ensure critical clinical data is processed first
• Priority Sorting: Dynamic prioritization based on clinical urgency and data freshness
• Subsystem Selection: Automatic routing to CardioAI Platform, IoMT Platform, or PACS/DICOM Platform

Load Balancing

Optimal resource distribution ensures maximum efficiency and consistent performance:

• Agent Distribution: Dynamic workload distribution across 7 specialized AI agents
• Resource Allocation: Intelligent compute resource management based on task complexity
• Throughput Optimization: Continuous monitoring and adjustment to maximize patient processing capacity

State Management

Real-time tracking of all clinical workflows from initiation to completion:

• Task Lifecycle Tracking: Complete audit trail of every clinical data processing step
• Status Monitoring: Real-time visibility into processing status across all subsystems
• Result Aggregation: Synthesis of outputs from multiple agents into comprehensive clinical reports

Event Broadcasting

Instant alerts and notifications ensure clinicians receive critical information immediately:

• Real-time Notifications: Instant push notifications for critical findings
• WebSocket Events: Low-latency event streaming to connected clients
• Alert Distribution: Multi-channel delivery (SMS, email, in-app) based on urgency

Error Recovery

Automatic failover and retry mechanisms ensure continuous operation:

• Automatic Retry Logic: Intelligent retry with exponential backoff for transient failures
• Fallback Strategies: Alternative processing paths when primary agents are unavailable
• Failure Handling: Graceful degradation and detailed error logging for troubleshooting

Metrics Collection

Comprehensive performance monitoring and analytics drive continuous improvement:

• Performance Monitoring: Real-time tracking of processing latency, throughput, and resource utilization
• Health Checks: Continuous monitoring of all agents and subsystem availability
• Analytics Tracking: Detailed usage analytics and clinical outcome tracking

Subsystem 1: CardioAI Platform - 7 Specialized AI Agents

The CardioAI Platform features seven specialized AI agents that work collaboratively to provide comprehensive cardiac analysis. Each agent is optimized for specific data types and clinical tasks, working in parallel to deliver rapid, accurate assessments.

1. ECG Agent - Advanced Electrocardiogram Analysis

The ECG Agent provides real-time analysis of electrocardiogram data with clinical-grade accuracy:

• STEMI/NSTEMI Detection: Automatic identification of ST-elevation and non-ST-elevation myocardial infarction with time-to-detection under 10 seconds
• Arrhythmia Classification: Detection of atrial fibrillation, ventricular tachycardia, bradycardia, and other rhythm abnormalities
• ICD-10 Coding: Automatic generation of appropriate diagnostic codes for billing and documentation

2. Echo Agent - Comprehensive Echocardiography Analysis

The Echo Agent processes ultrasound imaging data to assess cardiac structure and function:

• HFrEF/HFpEF Assessment: Differentiation between heart failure with reduced and preserved ejection fraction
• Valve Function Analysis: Quantitative assessment of aortic, mitral, tricuspid, and pulmonary valve function
• Ejection Fraction Calculation: Automated measurement of left ventricular ejection fraction using Simpson's biplane method

3. Lab Agent - Biomarker Analysis and Trend Detection

The Lab Agent analyzes laboratory values and identifies clinically significant patterns:

• Troponin & BNP Analysis: Interpretation of cardiac biomarkers in context of clinical presentation
• Lipid Profile Assessment: Comprehensive lipid analysis including LDL, HDL, triglycerides, and total cholesterol
• Biomarker Trends: Temporal analysis identifying concerning trends before they become critical

4. Risk Agent - Predictive Risk Assessment

The Risk Agent employs validated scoring systems to predict patient outcomes:

• TIMI & GRACE Scoring: Thrombolysis in Myocardial Infarction and Global Registry of Acute Coronary Events risk scores
• Mortality Risk: Short-term and long-term mortality prediction for acute coronary syndromes
• 10-Year CVD Prediction: Framingham and ASCVD risk scores for primary prevention

5. Diagnostic Agent - Evidence-Based Diagnostic Synthesis

The Diagnostic Agent integrates findings from all other agents to formulate comprehensive diagnoses:

• Evidence Synthesis: Integration of ECG, echo, lab, and risk data into unified clinical picture
• Differential Diagnosis: Ranked list of possible diagnoses with supporting evidence
• Decision Support: Clinical decision support aligned with ACC/AHA guidelines

6. Treatment Agent - Personalized Treatment Recommendations

The Treatment Agent generates evidence-based treatment plans tailored to individual patients:

• Protocol Generation: Automated creation of treatment protocols based on current guidelines
• Drug Recommendations: Medication selection considering patient-specific factors and contraindications
• Dosage Optimization: Personalized dosing based on renal function, weight, and other factors

7. Prognosis Agent - Outcome Prediction and Care Planning

The Prognosis Agent forecasts patient outcomes and recommends appropriate follow-up:

• Outcome Prediction: Statistical modeling of readmission risk and major adverse cardiac events
• Survival Analysis: Long-term survival prediction using validated prognostic models
• Follow-up Planning: Personalized follow-up schedules based on risk stratification

Subsystem 2: IoMT Platform - Real-Time Device Monitoring

The Internet of Medical Things (IoMT) Platform enables continuous patient monitoring through integration with wearable devices and remote monitoring equipment. The platform supports four communication protocols and provides sub-second alert latency for critical events.

Multi-Protocol Support

The IoMT Platform supports four industry-standard protocols ensuring compatibility with diverse device ecosystems:

• MQTT: Message Queue Telemetry Transport for efficient, reliable messaging
• HTTP/HTTPS: RESTful APIs for device configuration and data transmission
• CoAP: Constrained Application Protocol for low-power devices
• WebSocket: Full-duplex communication for real-time bidirectional data flow

Device Registration and Management

Seamless device onboarding ensures rapid deployment and patient association:

• Device Provisioning: Automated device setup with unique device identifiers
• Credential Generation: Secure certificate-based authentication for each device
• Patient Association: Binding of devices to patient records with audit trail

Telemetry Processing

Real-time data ingestion from wearables with intelligent processing:

• Real-time Ingestion: Continuous data streaming with 24/7 availability
• Stream Processing: Apache Kafka-based event streaming for high-throughput data processing
• Time-series Storage: Optimized storage for longitudinal vital sign trends

Alert Generation

Intelligent alerting ensures critical events receive immediate clinical attention:

• Anomaly Detection: Machine learning-based identification of abnormal vital sign patterns
• Threshold Violations: Configurable thresholds for heart rate, blood pressure, SpO2, and other parameters
• Alert Prioritization: Tiered alert system (critical, warning, informational) to prevent alert fatigue
• Sub-second Latency: Alert generation and delivery within 1 second of threshold violation

Device Monitoring and Health

Continuous monitoring ensures device reliability and data integrity:

• Connectivity Tracking: Real-time monitoring of device online/offline status
• Battery Status: Proactive alerts for low battery conditions requiring device charging
• Heartbeat Monitoring: Periodic health checks ensure devices are functioning properly

Subsystem 3: PACS/DICOM Platform - Medical Imaging Analysis

The Picture Archiving and Communication System (PACS) integrates seamlessly with existing radiology infrastructure, providing AI-powered analysis of cardiac imaging studies. The platform features six specialized agents working in parallel to process DICOM images and generate structured reports.

DICOM Ingestion

Standards-compliant medical image reception and metadata extraction:

• C-STORE Reception: DICOM C-STORE service class provider for receiving images
• C-FIND Queries: DICOM query/retrieve for locating prior studies
• Metadata Extraction: Automated extraction of patient demographics, study information, and acquisition parameters

Preprocessing

Image enhancement and quality optimization prepare images for AI analysis:

• Image Normalization: Standardization of intensity values and spatial resolution
• Quality Enhancement: Noise reduction and contrast optimization
• Artifact Removal: Detection and correction of motion artifacts and other image defects

Segmentation with 4 Parallel Agents

Automated structure identification using four parallel deep learning agents:

• Cardiac Chamber Segmentation: Delineation of left ventricle, right ventricle, left atrium, right atrium
• Vessel Detection: Identification of coronary arteries, aorta, and pulmonary vessels
• Myocardial Boundary Detection: Endocardial and epicardial contour tracing
• Parallel Processing: Four specialized agents working simultaneously for rapid analysis

Quantification

Precise cardiac measurements derived from segmented structures:

• Volume Calculations: End-diastolic volume (EDV) and end-systolic volume (ESV)
• Ejection Fraction Measurement: Automated EF calculation with confidence intervals
• Strain Analysis: Global longitudinal strain (GLS) and regional strain assessment

Specialized Analysis

Advanced imaging techniques providing additional diagnostic information:

• T1/T2 Mapping: Cardiac MRI tissue characterization for fibrosis and edema
• Calcium Scoring: Agatston score calculation from CT angiography
• Perfusion Analysis: Myocardial blood flow quantification from stress/rest imaging

Report Generation

Automated reporting with industry standards compliance:

• DICOM SR Creation: Structured reporting in DICOM Structured Report format
• PDF Export: Human-readable reports with key images and measurements
• HL7 Integration: Automated delivery of results to EMR systems via HL7 messaging

AI-Powered Risk Calculators - 5 CVD Event Predictors

Cardio AI incorporates five validated cardiovascular disease risk calculators, each powered by AI to provide superior predictive accuracy. All calculators deliver predictions with 95% confidence intervals across 1-year, 5-year, and 10-year time frames, with results categorized into four risk levels aligned with AHA guidelines.

Key Features Across All Calculators:

• 95% Confidence Intervals: All predictions include statistical confidence bounds
• 3 Time Frames: 1-year, 5-year, and 10-year risk predictions
• 4 Risk Categories: Low, moderate, high, very high risk stratification
• AHA Guidelines Aligned: 100% compliance with American Heart Association clinical practice guidelines

Complete Cardiac Workflow - 6-Step Integrated Process

Cardio AI orchestrates a comprehensive six-step workflow that seamlessly integrates all subsystems and agents to deliver complete cardiac assessments. The Master Orchestrator coordinates each step in real-time, ensuring data flows efficiently from initial vital signs through final treatment recommendations.

Step 1: IoMT Vitals - Real-Time Monitoring

Continuous collection of vital signs from wearable devices and remote monitoring equipment. The IoMT Platform processes heart rate, blood pressure, SpO2, and other parameters in real-time, triggering alerts for threshold violations.

Step 2: ECG Analysis - Arrhythmia Detection

The ECG Agent analyzes electrocardiogram data for STEMI/NSTEMI, arrhythmias, and conduction abnormalities. Results are immediately available to the Diagnostic Agent for integration into the clinical picture.

Step 3: Risk Calculation - 5 CVD Calculators

The Risk Agent applies all five cardiovascular risk calculators (AMI, Stroke, Heart Failure, SCD, AFib) to generate comprehensive risk profiles with 1/5/10-year predictions and 95% confidence intervals.

Step 4: Imaging - DICOM Analysis

The PACS/DICOM Platform processes cardiac imaging studies through six specialized agents, generating quantitative measurements including ejection fraction, chamber volumes, and strain analysis.

Step 5: Diagnosis - Evidence Synthesis

The Diagnostic Agent synthesizes findings from all previous steps (IoMT vitals, ECG, risk scores, imaging, lab values) to formulate differential diagnoses with supporting evidence.

Step 6: Report - Treatment Plan

The Treatment and Prognosis Agents collaborate to generate comprehensive treatment recommendations, medication protocols, and follow-up plans. The final report integrates all findings into a structured, actionable clinical document.

Platform Performance Characteristics

For technical demonstrations or platform access:

Interactive Technology Explorer: cardioai-tech-explorer.vercel.app

Request Demo: product-demo-request-form.vercel.app

Technical Inquiries: [email protected]