The Engine of Predictability
Deep-dive into the proprietary clinical intelligence stack powering the post-EHR era.
Predictive Risk Engine
Our continuously running inference model analyzes 5,000+ data points per patient per second to forecast deterioration before clinical signs appear.
Key Capabilities
- Sepsis Forecast: up to 48 hours notice with 96% sensitivity.
- Cardiac Event Horizon: Real-time arrhythmia prediction from telemetry stream.
- AKI Prediction: Acute Kidney Injury risk scoring based on real-time labs and fluids.
Explainable AI (XAI) Architecture
We solve the "Black Box" problem. Every alert generated by the Predictive Risk Engine comes with an "Evidence Chain"—a human-readable list of contributing factors (e.g., "Rising Lactate + Dropping BP trend").
> Temp > 38.2°C
> WBC Trend: +15% over 4h
The Pharmacogenomic Safety Net
Before any medication is ordered, Elenthor checks the patient's genetic profile against the drug's metabolic pathway (e.g., CYP2D6, CYP2C19) to prevent adverse reactions.
Genomic Intelligence Layer
We treat genomic data not as a static PDF report, but as active code that interacts with every clinical decision.
Core Functions
- Real-Time PGx Checks: Automatic dosage adjustments for poor/ultra-rapid metabolizers.
- Polygenic Risk Scoring: Background calculation of long-term risks (CAD, Diabetes Type 2).
- Oncology Matching: Automated matching of tumor mutations to targeted therapies and clinical trials.
Elenthor Clinical Copilot
A context-aware multimodal LLM designed specifically for the clinical environment. It listens, understands, and writes, allowing doctors to focus on the patient.
Autonomous Documentation
- Ambient Scribing: Generates structured SOAP notes significantly faster than human typing.
- Coding Automation: Derives ICD-10 and CPT codes instantly from the clinical narrative.
- Order Extraction: "Nurse, let's get a CBC and start fluids" automatically queues the orders for signature.
Multimodal Patient Model
Elenthor doesn't just read text. It "sees" medical imaging and "reads" raw telemetry waveforms, integrating them into a single latent representation of the patient's health state.
See the Core in Action
Full technical whitepapers and API documentation available upon request.