Everyone knows that sepsis is a big problem in healthcare.
Everyone wants to find the right algorithms to identify sepsis risk to allow for early intervention.
Not all sepsis algorithms are created equal.
These are some of the lessons we’ve learned as even some of the top EHR companies have tried to address this problem and ran into trouble. The question remains on whether EHR data is sufficient to identify sepsis risk or whether something more is needed.
In a recent video interview I did with Prashant Natarajan, VP of Strategy and Products, H2O.ai,
Niki Athanasiadou, Data Scientist and Healthcare AI Product Manager at H2O.ai, and Ljubomir Buturovic, VP, Machine Learning at Inflammatix, we dive into this topic and a diagnostic approach to sepsis prediction paired with machine learning and AI.
It’s fascinating to see Inflammatix and H2O.ai cooperate in analyzing different RNA gene expression profiles using state-of-the-art machine learning. Inflammatix is developing a 30 minute point-of-care test that goes from blood sample to an AI analyzed result that determines a patient’s risk for infection, cause (bacterial or viral), and level of severity.
Along with discussing the solution, we also talk more broadly about the use of AI and machine learning in healthcare. They share where we are at in applying these technologies to healthcare and where we can expect to see a big impact. Plus, they share what needs to be done to ensure that we can trust the results of AI.
Check out the video to learn more about a unique sepsis solution and how machine learning and AI are providing better results:
Learn more about H2O.ai: https://www.h2o.ai/
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