Improving outcomes for critical care patients using AI
We imagine a world where clinical teams can easily use AI to provide the best possible care for their critically injured and ill patients.
Improving patient outcomes for trauma patients using AI
What’s The Problem?
Physical trauma is the leading cause of death for individuals up to the age of 45 and costs $130 billion annually in medical care.
Every trauma case has its own avalanche
of new data, decisions, and problems
Multi Sources of real-time patient data
This leads to high subjectivity and variability, which impacts patient
outcomes and causes inefficient resource utilization
How We Are Solving It?
predictions and precise data, helping them to make better decisions
Shares real-time, patient specific data
Integrated in existing EHR software
UX built for trauma and ICU workflows
Provides real-time risk predictions
Intuitive, easy-to-use user interface
AI models built using only critical care data
Here’s how it looks in practice:
19 year-old patient who was involved in a high speed motorcycle accident without a helmet;
he is somnolent and has a weak radial pulse, arriving in ICU in 5 minutes.
Our AI algorithm will identify two key things:
Assesses the risk of death of this patient in the next 48 hours - indicating that risk to be high at 56%
Outlines the primary individualized reasons for that risk - elevated lactate and AST indicating liver injuries