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NeuroSight ICP: AI-Assisted, Real-Time Forecasting of Intracranial Pressure Crises

Published:
Lead Inventor: Alexander Steep
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SUMMARY

NeuroSight ICP is a bedside-ready, AI-assisted forecasting system designed to predict intracranial pressure (ICP) crises roughly 30 minutes before onset using continuous neuro-monitoring data. It combines interpretable statistical modeling with Hidden Markov Model (HMM)-aware features to generate actionable risk scores and alerts that can be tuned to each unit’s tolerance for false alarms.

The Unmet Need: Severe TBI care is often reactive, with clinicians waiting for ICP threshold breaches and dealing with noisy ICU telemetry and alarm fatigue.

Severe traumatic brain injury management often remains reactive, with clinicians intervening only after ICP thresholds have already been breached leading to worse outcomes for patients. Existing approaches also face practical barriers including noisy ICU telemetry, inconsistent crisis definitions, limited deployment readiness, and alarm fatigue, leaving a need for a clinically usable forecasting tool that provides early warning without overwhelming care teams.

The proposed solution: AI-Assisted forecasting to anticipate ICP crises before they occur enables clinicians to react preemptively

NeuroSight ICP continuously receives bedside monitoring data, including ICP and optional signals such as PbtO₂ and other vitals to engineer short term trends and context features, and then predicts the probability of an ICP crisis within the next 30 minutes. The final model is a compact 6-feature logistic regression framework enhanced by HMM-derived state information, with alerts refreshed on a fixed cadence and thresholds adjustable to match local workflow and false-positive tolerance. This enhanced prediction enables clinicians to react before the patient reaches critical thresholds.

NeuroSight ICP addresses a persistent unmet need in neurocritical care by delivering interpretable, real-time forecasting of ICP crises in a format designed for bedside deployment. Its combination of clinical usability, rigorous data handling, and tunable alerting positions it as a promising solution for healthcare partners seeking to improve severe TBI monitoring, reduce secondary brain injury risk, and operationalize predictive analytics in the ICU.

 

ADVANTAGES

ADVANTAGES

  • Clinically actionable early warning

  • Interpretable and auditable

  • Deployment-ready alerting

  • Operationally measurable

  • Robust to real ICU data

  • Portable and extensible

APPLICATIONS

  • Neurocritical care units
  • ICU bedside monitoring platforms
  • Hospital quality improvement programs
  • Clinical outcomes research
  • Expanded multimodal monitoring
  • Patent Pending
  • Proof of Concept