Clinical Intelligence for
Modern Healthcare Systems
Transform clinical, genomic, and operational healthcare data into predictive intelligence, decision support, and population-scale insights.
Clinical Intelligence Infrastructure
Production-grade data pipeline from clinical source systems to decision support, deployed in NHS trust environments.
Ingest
FHIR R4, HL7 v2, DICOM, and flat-file ingestion with validation and quality checks
Process
Clinical data warehouse with specialized genomics, oncology, and operational data marts
Intelligence
Validated AI/ML models for classification, survival analysis, and demand forecasting
Production-Deployed Intelligence
Each module addresses a specific clinical or operational need, validated in NHS environments. Screenshots shown are from actual deployed instances.
Oncology AI
Breast Cancer Classification
AI-assisted worklist prioritization for breast lesion assessment in radiology reporting workflows
Processes histopathology and radiology images through validated classification models to support reporting prioritization. Designed as an operational efficiency tool, not a diagnostic device.
- →Worklist prioritization based on radiological suspicion scoring
- →Standardized BI-RADS classification support for reporting radiologists
- →Full audit trail maintained for clinical governance review
Genomics Intelligence
Genomic Variant Annotation
Clinical interpretation support for genomic variants with evidence-based pathogenicity assessment
Integrates population databases (gnomAD, ClinVar), in-silico prediction tools, and published clinical evidence for variant classification in accordance with ACMG guidelines.
- →ACMG-compliant variant classification with evidence aggregation
- →Reduction in manual literature curation time
- →Auditable decision trail with evidence provenance
Gene Expression Analysis
Transcriptomic profiling for disease subtyping and treatment response research
Processes RNA-seq data through normalized expression pipelines with integrated clinical annotation support for research cohort analysis.
- →Molecular subtype identification for research cohorts
- →Differential expression analysis with clinical variable correlation
- →Research-grade visualizations and export capabilities
Biostatistics
Kaplan-Meier Survival Analysis
Patient survival probability estimation across treatment groups and time periods
Generates publication-grade survival curves with confidence intervals, log-rank testing, and multi-cohort comparison capabilities.
- →Evidence-based treatment evaluation support
- →Clinical audit and service evaluation tools
- →Research publication-quality visualizations
Cox Proportional Hazards Model
Multivariate survival analysis identifying independent prognostic factors
Calculates hazard ratios with covariate adjustment for complex clinical datasets. Supports research and clinical audit applications.
- →Risk factor quantification with adjusted hazard ratios
- →Prognostic model development for research cohorts
- →Confounder-adjusted outcomes analysis
NHS Operations
RTT Waiting List Analytics
Referral-to-Treatment pathway performance monitoring and capacity analysis
Processes NHS waiting list data extracts to provide specialty-level RTT performance visibility, breach risk identification, and capacity constraint analysis.
- →Specialty-level RTT performance dashboards
- →18-week breach risk flagging
- →Capacity and demand gap visualization
Demand Forecasting
Predictive modeling of clinical demand across outpatient and diagnostic services
Applies time-series forecasting models to historical activity data with demographic trend and seasonal adjustment factors.
- →30/60/90-day activity forecasts by specialty
- →Seasonal pattern identification
- →Population growth-adjusted projections
Predictive Medicine
Diabetes Risk Prediction
Population-level risk stratification for type 2 diabetes prevention programmes
Processes primary care data extracts through validated risk models (QDiabetes, Finnish Diabetes Risk Score) to identify high-risk patient cohorts for targeted prevention.
- →Risk-stratified patient cohort identification
- →Prevention programme eligibility flagging
- →Population health needs assessment support
Core Platform
Clinical Data Quality Engine
Automated assessment and profiling of clinical data completeness, consistency, and validity
Profiles incoming clinical datasets against configurable quality rules, generates completeness reports, and identifies data quality issues requiring remediation.
- →Data quality dashboards with completeness metrics
- →Automated quality rule validation
- →Data preparation time reduction for analytics teams
Complete Platform Gallery
All production interfaces from deployed modules. Click to expand any screenshot for detailed view.
Breast Cancer Classification: AI-assisted diagnostic prioritization with histopathology integration
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Waiting List & Capacity Intelligence
Operational analytics designed for NHS trust performance management, capacity planning, and constitutional standard compliance.
Non-admitted pathway within 18 weeks
Predicted shortfall vs demand next quarter
Reduction since module deployment
RTT Analytics
Monitors referral-to-treatment performance across all specialties with automated breach prediction, specialty-level drill-down, and commissioner reporting.
- • 18-week compliance tracking
- • Breach risk alerts
- • Specialty comparison
Capacity Modelling
Predictive modelling of clinical capacity requirements based on historical demand patterns, demographic projections, and seasonal variation.
- • Clinic slot optimization
- • Staffing requirement forecasts
- • What-if scenario planning
Demand Forecasting
Time-series forecasting of clinical demand across outpatient, inpatient, and diagnostic services with demographic adjustment factors.
- • 30/60/90-day forecasts
- • Seasonal pattern detection
- • Population growth adjustment
All NHS operational analytics are designed for procurement evaluation. Modules can be deployed on-premise or within HSCN-connected cloud environments. Data processing complies with NHS Digital Data Security and Protection Toolkit requirements.
Module Performance & Validation
Independent validation results and platform capability assessments. Active NHS trust pilot evaluations are in progress — confirmed deployment outcomes will be published following evaluation completion.
Breast cancer reporting worklist prioritization
Rising breast cancer referral volumes are creating reporting backlogs in radiology departments. Clinical teams need tools to prioritize high-suspicion cases within existing PACS workflows.
The NeuralEdge Breast Cancer Classification module processes DICOM images through an ensemble of validated classification models to assign suspicion scores. These scores feed into the reporting worklist to surface high-priority cases without requiring changes to existing PACS infrastructure.
- →Model AUC of 0.94 on independent test sets (multi-site validation in progress)
- →Designed to integrate with existing NHS PACS/RIS reporting workflows
- →Full audit trail with model confidence scores for clinical governance
Automated genomic variant classification for clinical scientist workflows
Growing genomic test volumes are increasing the manual variant curation burden on clinical scientists. Automated classification tools are needed to support ACMG-compliant variant interpretation at scale.
The NeuralEdge Variant Annotation module aggregates evidence from public databases (ClinVar, gnomAD), in-silico predictors, and published literature to produce ACMG-compliant variant classifications with full evidence provenance.
- →Automated ACMG classification with evidence provenance for all criteria
- →Designed to reduce manual curation time for clinical scientists
- →Exports structured variant reports compatible with GLH reporting systems
Transparency note: Results shown are from independent platform validation using de-identified clinical datasets. Active NHS trust pilot evaluations are underway. Confirmed deployment outcomes with named trust references will be published upon completion of evaluation periods and receipt of written permission from participating trusts.
Enterprise-Grade Clinical Data Protection
Infrastructure designed for the requirements of NHS procurement, clinical governance, and information governance frameworks.
UK GDPR Alignment
Platform architecture designed to support UK GDPR compliance requirements for health and care data processing. Includes data minimization, purpose limitation, and retention controls.
- ✓Data processing impact assessments
- ✓Right of access workflows
- ✓Data minimization controls
Role-Based Access Control
Granular permission model supporting clinical, operational, research, and administrative roles with attribute-based access policies.
- ✓Clinical role profiles
- ✓Department-level scoping
- ✓Break-glass emergency access
Audit Logging
Comprehensive audit trail capturing all data access, model inference, and configuration changes with tamper-evident logging.
- ✓Immutable audit records
- ✓Access pattern monitoring
- ✓Clinical safety event logging
FHIR Interoperability
Native FHIR R4 support for integration with NHS Spine, regional shared care records, and trust EPR systems.
- ✓FHIR R4 RESTful API
- ✓HL7 v2 message support
- ✓DICOM integration gateway
Deployment Flexibility
Support for on-premise, HSCN-connected cloud, and hybrid deployment models to meet varying trust infrastructure requirements.
- ✓On-premise deployment
- ✓HSCN-connected cloud
- ✓Air-gapped environment support
Clinical Safety
Platform designed with clinical safety principles. All AI/ML modules produce auditable outputs for clinical review, not autonomous decisions.
- ✓Human-in-the-loop design
- ✓Confidence score transparency
- ✓Clinical safety officer role
Important: This platform supports clinical decision-making but does not replace clinical judgment. All AI/ML outputs are designed for human review. No regulatory certification claims are made. Prospective customers should conduct their own compliance assessment for their specific use case and deployment environment.
Implementation & Clinical Adoption Services
Specialized support for NHS trust onboarding, system integration, and clinical workflow adoption. Not a consulting firm — a deployment partner.
System Onboarding
Technical integration with trust EPR systems, data source connection, and FHIR endpoint configuration.
Integration Support
Data mapping, transformation pipeline configuration, and quality validation rule setup.
Workflow Mapping
Clinical pathway analysis to identify integration points for AI/ML model outputs in existing workflows.
Training & Enablement
Clinical and operational staff training on platform capabilities, interpretation of outputs, and governance processes.
Pilot Deployment
Staged rollout with defined success criteria, performance monitoring, and clinical safety evaluation.
Adoption Optimization
Usage analytics, workflow refinement, and expansion planning based on pilot outcomes.
Implementation services are designed to accelerate time-to-value for NHS trust deployments. Services are scoped per engagement with defined deliverables and handover to trust operational teams.
Why NeuralEdge
Addressing the convergence of NHS operational pressure, genomics adoption, and oncology AI — an underserved mid-market healthcare analytics opportunity.
Market Convergence
Three structural shifts are creating demand for integrated clinical intelligence: NHS elective recovery pressure requiring operational analytics, genomic medicine service expansion generating variant interpretation volume, and oncology AI adoption reaching clinical validation stage.
Open-Core Platform Strategy
Core clinical data quality and FHIR infrastructure available as foundation, with specialized modules for oncology, genomics, and NHS operations providing the commercial differentiation. Enables rapid trust-specific configuration.
Consulting → SaaS Transition
Implementation services provide initial revenue, trust relationships, and real-world validation. Transition path to SaaS subscriptions as platform matures and procurement frameworks adapt to cloud-based clinical software.
Multi-Revenue Model
Category Potential
Path to £100M+ ARR clinical intelligence category
Addressing the gap between legacy analytics vendors and research-only AI platforms with production-deployed, procurement-ready clinical intelligence infrastructure.