Real-Time ML Pipeline for Healthcare

The Challenge

NeuralWorks needed a real-time ML system to analyze patient vitals and lab results, detecting early signs of deterioration. The system had to meet HIPAA compliance, process data from 50+ hospital systems in different formats, and deliver predictions to clinicians within 500ms.

Our Approach

1. 1Designed a HIPAA-compliant event-driven architecture with end-to-end encryption
2. 2Built data ingestion adapters for HL7 FHIR, CSV feeds, and proprietary hospital APIs
3. 3Implemented a feature store for real-time feature computation from streaming patient data
4. 4Trained and validated ML models on 2 years of de-identified patient data with clinician oversight
5. 5Deployed models behind a low-latency inference service with sub-100ms prediction times
6. 6Built monitoring dashboards showing model performance, alert rates, and clinician response times

The Results

The system processes data from 50+ hospitals in real-time, generating early warning alerts with 87% precision. Clinician response time to deteriorating patients improved by 40%. The platform has been operational for 18 months with zero HIPAA incidents.