Predictheon

The ideas behind Predictheon started in 2015 when a group of medical doctors, anesthesiologists to be specific, together with math modelers, and computer engineers decided to move forward their prior research track. The original goal was to create a new concept in patient care management, one that seeks to integrate predictive analytics with real-time monitoring, in order to give clinicians meaningful information about a patient’s future behavior. Such information would allow an anesthesia provider to anticipate a clinically significant change, or possibly an upcoming negative event before it occurs. This concept arose from the desire to better understand how the current state of the patient will change in the next 5 or 10 minutes from now, allowing the anesthesia provider to proactively act ahead of time, to prevent a potentially severe adverse side effect before it happens. The concept expanded to other areas of healthcare where we are actively searching for predictive solutions (perioperative blood management, altered postoperative cognition, critical care, oncology, …). Predictheon was created as a company in 2019.
We verified our idea by continuously collecting “outcome-oriented” high-resolution data from a vast number of patients, analyzing those data under a population perspective, using classical modeling or AI-derived methods, and have now come up with a powerful “predictive engine” based on mathematical models describing the relations between patients and outcomes. When we apply our unique solution to a new patient, our models can predict future behavior, including potentially severe side effects before they happen. Predictheon’s individualized patient care now results in optimal decision making and increased patient safety during a medical procedure that requires the patient to have sedation or general anesthesia and will expand into other areas of patient care.

Company’s Keywords:

data analysis, mathematical modeling, predictive analytics, personalized medical care, improved patient outcomes, signal analysis, simulation, sedation, general anesthesia, predictive monitoring, perioperative blood management, pharmacologic modeling, physiologic modeling, machine learning, nonlinear mixed effects modeling, oncology, cognitive function