Breakthrough Results!

We're excited to announce major breakthroughs from our research! Picture our team as engineers in a high-tech workshop, fine-tuning not one, but four groundbreaking algorithms. These tools are our response to the critical challenge of diagnosing serious infections and sepsis quickly and accurately in emergency medicine, where every second matters.

In the fast-paced environment of emergency medicine, our newly developed tools will act like expert co-pilots. They will provide real-time insights to doctors, guiding them to make lifesaving decisions.

What's under the hood of these advanced co-pilots? A powerful engine known as machine learning. These innovations will act like expert co-pilots for doctors, offering real-time insights with the precision of a racing car, thanks to the power of machine learning. This technology, a core part of artificial intelligence, enables our algorithms to learn from  vast amounts of data, improving their ability to guide life-saving decisions.

To track the performance of our high-speed innovations, we use a metric called the Area Under the Curve (AUC). Think of it as the lap time for our algorithms; the closer it is to 1.0, the more accurately they can predict the best course of action.

Amongst our lineup, one champion emerges – the "TRIAGE MODEL." This algorithm has proven itself, demonstrating exceptional skill in predicting whether a child needs intravenous antibiotics from the moment they arrive in the emergency department.

Closely followed, the "Critical Care Model" crosses the finish line with impressive precision. It adeptly predicts the need for emergency interventions like fluid resuscitation or breathing support. Picture this tool as the emergency response team in the pit lane, always on standby, ready to spring into action with life-saving precision the moment a child arrives needing urgent care.

Hot on the heels of our frontrunners, the "Serious Infection Model" steps in with a focused approach. It serves as a crucial tool in our arsenal, highlighting children who face the high threat of their condition worsening and urgently need intervention.

This model efficiently determines which patients are likely to need hospitalization for intravenous antibiotics for a minimum of two days. Demonstrating good accuracy, it guides complex medical decisions with the precision of  a pro racer navigating a complex, challenging terrain.

Stay tuned as our team continues to enhance these algorithms and develop software that integrates these models for real-world use...