Peer-reviewed research, engineering deep dives, and clinical AI breakthroughs from the NeuralCare team.
Our research team presents a landmark study across 2.1 billion de-identified patient records using federated learning — no data ever left institutional boundaries. The transformer architecture identifies subtle pre-symptomatic biomarker patterns up to 48 months before clinical presentation.
Sepsis kills 270,000 Americans annually. We break down the deep learning pipeline that identifies sepsis onset from subtle vitals and lab trend patterns before conventional SOFA scoring triggers.
A deep dive into our GPU-accelerated inference stack — TensorRT optimization, ONNX runtime, and the batching strategies that deliver sub-50ms latency across 340+ hospital systems simultaneously.
How we trained on 2.1 billion patient records across multiple continents while ensuring zero raw data egress. Our differential privacy implementation and gradient aggregation protocol explained.
Step-by-step walkthrough of EHR integration via FHIR R4 and HL7 v2.x. Covers Epic, Cerner, and Meditech connectors with real configuration examples from production deployments.
Led by Andreessen Horowitz with participation from Google Ventures and existing investors, the round will fund expansion into APAC markets, regulatory clearance in five new jurisdictions, and 80 new engineering hires.
NeuralCare's longitudinal EHR analysis identifies subtle biomarker drift patterns predictive of malignancy up to four years before conventional diagnosis. Published in Nature Medicine, peer-reviewed by 12 independent oncologists.
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