TB-AI: advanced analytics for the management of traumatic brain injury

Traumatic Brain Injury (TBI) is a global health problem, representing the first cause of death in young adults and a major cause of disability across all ages. Treatment of TBI mostly aims at preventing and treating secondary brain injury, a series of inflammatory, ischemic, and mechanic events that can follow the initial traumatic event, leading to additional brain damage or even death. For this, invasive neuromonitoring is applied. We developed a prototype decision-support software that uses advanced analytics to display and interpret neuromonitoring signals in order to provide valuable information for the treatment of severe TBI to clinicians and gives an early forewarning for impeding catastrophic events. The software is the first of its kind and has the potential to revolutionize clinical management of TBI. The goal of this project is to test safety and accuracy of this software in a multi-center setting, and to define the regulatory roadmap towards registration as a classified medical device.

Keywords:Decision-support system, Artificial intelligence, Traumatic brain injury, Neuro-monitor, Advanced Analytics

Disciplines:Medical intensive care, Machine learning and decision making, Data mining