From early detection to population health management โ every NeuralCare capability runs on GPU-accelerated infrastructure with sub-50ms inference latency.
Transformer-based models trained on 500M+ de-identified patient records detect disease signals up to 48 months before conventional presentation.
14 disease categories ยท AUC 0.94+TensorRT-optimized serving on A100/H100 clusters. 4.2M+ inferences per hour with sub-50ms latency โ fast enough for point-of-care decision support.
47ms avg latency ยท 4.2M inferences/hrTrain models across 340+ hospital nodes with zero patient data egress. Differential privacy with ฮต-DP guarantees on every gradient update.
2.1B records ยท 0 data egressEpic Smart App, Cerner PowerChart widget, Oracle Health module โ NeuralCare surfaces insights inside workflows clinicians already use, zero new logins.
200+ EHR connectors ยท FHIR R4Every risk flag includes SHAP-based attribution showing which biomarkers, labs, and historical patterns drove the prediction โ auditable and defensible.
FDA 21 CFR Part 11 compliantCSRD and GRI-aligned reporting dashboards. Track disease burden trends, intervention efficacy, and health equity metrics across your entire patient population.
CSRD ยท GRI ยท HIPAA compliantFrom ONNX Runtime model execution to TensorRT INT8 quantization, every inference pipeline is hardware-optimized for clinical-grade latency.
| Capability | NeuralCare AI | Rule-Based CDSSs | Generic ML Platforms |
|---|---|---|---|
| Early detection (12+ mo ahead) | โ | โ | โ |
| Sub-50ms inference latency | โ | โ | โ |
| Federated learning (no data egress) | โ | โ | โ |
| Native Epic/Cerner integration | โ | Partial | โ |
| Explainable AI (SHAP attribution) | โ | โ | Partial |
| HIPAA + GDPR + SOC 2 | โ | Varies | Varies |
| Continuous federated model updates | โ | โ | โ |
| CSRD/GRI population reporting | โ | โ | โ |