DiviScan analyzes dozens of organ-system endpoints simultaneously through a 9-layer diagnostic engine, identifying patient deterioration significantly earlier than conventional early warning scores. Built on multi-knowledge-base inference, validated against MIMIC-IV critical care data.
Not a single-variable scoring system. DiviScan layers biomarker ingestion, multi-knowledge-base querying, phenotype mapping, ML inference, and utility-weighted decision logic into a unified clinical intelligence pipeline.
Multi-source lab and vitals intake with normalization across organ-system panels. Structured for downstream inference.
Organ-system panel decomposition — hepatic, renal, cardiac, metabolic, hematologic — with cross-panel correlation mapping.
Parallel lookup across HPO, OMIM, and clinical ontologies. 1M+ phenotype-gene associations for differential enrichment.
Translates abnormal results into standardized phenotype terms. Maps biomarker deviations to known clinical phenotypes.
Five trained disease models (CKD, liver disease, diabetes, sepsis, heart failure) generate probability scores from feature vectors.
Proprietary decision layer applying utility-weighted thresholds — not raw probability cutoffs. Context-sensitive alerting that reduces alarm fatigue.
Integrates signals across organ systems to detect multi-system deterioration patterns invisible to single-variable monitors.
Composite acuity scoring combining ML outputs, utility gates, and temporal biomarker trajectories into actionable risk tiers.
Structured output with organ-level breakdowns, confidence intervals, phenotype-gene evidence trails, and suggested next-step diagnostics.
Traditional early warning systems rely on a handful of vital signs. EHR-embedded tools apply raw probability thresholds. DiviScan operates on a fundamentally different architecture.
| Capability | NEWS / MEWS | Epic Sepsis Model | DiviScan |
|---|---|---|---|
| Input Variables | 6–7 vital signs | EHR data fields | Dozens of organ-system endpoints |
| Scoring Method | Aggregate threshold | Single-model probability | Utility-weighted multi-model |
| Knowledge Bases | None | None | HPO, OMIM, clinical ontologies |
| Disease Coverage | General deterioration | Sepsis only | 5 models + cross-organ synthesis |
| Alert Logic | Fixed threshold | Probability cutoff | Utility Gate (context-sensitive) |
| Phenotype Inference | No | No | 1M+ phenotype-gene associations |
| Alarm Fatigue | High | High | Reduced via utility weighting |
DiviScan's multi-layer architecture serves distinct but complementary clinical intelligence needs.
Identify why trials fail before they fail. DiviScan's simulation engine models biomarker trajectories across trial arms, detecting subpopulation signals and endpoint risks that traditional DSMB reviews miss.
Move beyond NEWS/MEWS. DiviScan processes routine lab panels and vitals through its 9-layer engine to surface multi-organ deterioration patterns before they become critical events.
DiviScan's performance is validated against real-world critical care data. We are transparent about our stage — these are demonstration-level results with clear clinical signal.
DiviScan's utility-weighted diagnostic methodology is protected under USPTO Provisional Patent #63/706,309. The core innovation — utility gate scoring applied to multi-knowledge-base clinical inference — is proprietary to RESSS Global Holdings LLC.
We believe in transparency. DiviScan's HyperCore OS is operational software with demonstrated capabilities — not a concept deck. Here is exactly where we stand.
Whether you're evaluating trial rescue capabilities or early warning infrastructure, we'd like to show you what DiviScan can do with your data.
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