Real-time patient monitoring, diagnostic support and operational optimization for hospitals and national healthcare systems

HEAL-Net is an energy-efficient AI module designed specifically for healthcare environments.
It supports:

• – real-time patient state monitoring,
• – diagnostic decision support,
• – hospital- and network-level workflow optimization,
• – and more stable, predictable operation across healthcare infrastructures.

Using Resonant Intelligence’s deep structural pattern analysis, HEAL-Net identifies meaningful correlations across large volumes of clinical data (EHR, sensors, lab results, imaging metadata, workflow logs). This enables at least 30–40% improvement in operational efficiency, reaction time and system stability.

What does HEAL-Net do?

HEAL-Net operates across three core layers:

1. Patient State Pattern Detection

• – early detection of abnormal vital-sign patterns
• – prediction of deterioration risk
• – early warning before escalation
• – continuous monitoring in real time

2. Diagnostic Support

• – unified interpretation of lab and examination data
• – pre-processing and pattern extraction from imaging workflows
• – clinical decision-support suggestions
• – patient-pathway optimization based on real-time context

3. Institutional & Network Workflow Optimization

• – forecasting of ward occupancy and resource demand
• – optimization of staff and diagnostic resource allocation
• – emergency and shift workload balancing
• – stabilization of patient flow across departments

Key advantages

• – at least 30–40% improvement in operational efficiency
• – earlier detection of critical patient changes
• – faster clinical response times
• – improved diagnostic accuracy through AI-supported insight
• – reduced overload and emergency bottlenecks
• – easily integrable into existing healthcare IT systems
• – usable in hospitals, clinics, labs and national networks

Where can HEAL-Net be deployed?

• – hospitals and clinical departments
• – emergency and intensive care units
• – national healthcare information systems
• – outpatient care and telemedicine
• – diagnostic laboratories
• – healthcare IoT ecosystems
• – elderly-care and home-monitoring environments

Why is it safe and compliant?

• – does not require new types of patient data
• – builds on existing EHR and healthcare systems
• – fully transparent, auditable decision logic
• – complies with healthcare data-protection standards
• – can be deployed gradually and modularly

Integration with the AVA ecosystem

HEAL-Net integrates with:

• – AVA Core – central orchestration and system logic
• – RCF-LIM – efficient execution of healthcare AI models
• – RCF-Secure – protection of sensitive health data
• – ADC-Optim – energy-efficient data-center operation
• – RI-Net – intelligent coordination across multiple institutions

Together, they form a scalable, energy-efficient healthcare intelligence infrastructure.

Project status

• – ready-to-start project
• – suitable for hospital- and national-level pilot deployments
• – low integration risk
• – significant societal value and impact potential