Technology
Regenesis-OS reads the structure of physiological signals, not just their values. Collapse is preceded by a measurable loss of order across the vital signs hospitals already monitor.
What We Measure
We quantify how organized a patient's physiology is, moment to moment. As control degrades, three properties move together, well before any single number crosses an alarm threshold.
Healthy regulation produces structured, predictable signals. As systems destabilize, that structure dissolves into randomness. We track the climb in signal entropy as an early marker of failing control.
Beat to beat and breath to breath, dispersion increases as the body loses its ability to hold a stable operating point. Growing variance signals reserve being exhausted.
In health, heart rate, respiration, and blood pressure move in concert. Disorder shows up as a breakdown in that coordination across vital signs, ahead of overt deterioration.
The specific mathematics that turn these properties into a calibrated risk estimate are proprietary. What matters clinically is the result: a probability that strengthens as an event approaches.
The Early-Warning Curve
The disorder signal sharpens in the hours before collapse. Performance is strong far out and becomes decisive close in, giving clinicians a widening, then tightening, window to act.
AUC, the area under the ROC curve, summarizes how well the model separates patients who will deteriorate from those who will not. 1.0 is perfect, 0.5 is chance.
Hours before event
Deployment
The model runs on routine vital-sign streams from existing monitors. There is no new bedside hardware to buy, install, or maintain. It reads the signals already flowing through the unit.
No new bedside hardware. Software layered onto the data your monitors already produce.
Calibrated probabilities. Output is a clinically interpretable risk, suitable for direct display.
Bias-audited pipeline. Audited end to end for five distinct sources of bias.
Performance was measured on a cohort of 1,258 ICU stays, matched on care unit and timing, and held out throughout development. External results came from separate hospital systems in the eICU database.
We are opening hospital pilot partnerships and an investor conversation.