#sepsis prediction models are inherently flawed. Read key takeaways from our recent @SepsisAlliance webinar exploring how to identify patients at risk of sepsis with the fewest false alarms.
https://t.co/lRA5WfkTgJ
From @JAMANetworkOpen: eCART outperformed the other #AI and non-AI early warning scores, identifying more deteriorating patients with fewer false alarms and sufficient time to intervene.
https://t.co/DPh3Fqk9TO
Does an AI/ML model provide more accurate warning of clinical deterioration than older models (logistic regression or point-based) among >360,000 hospitalized patients in 7 hospitals?
Yes. eCART (@AgileMD) performed best; EPIC (EDI) was one of the worst.
https://t.co/mfGZ0Ub5Tv by @dpedelson and colleagues
Editorial https://t.co/rBrWde86UO by @AmolAVerma
How can AI predict complications in hospitalized patients? Medical Grand Rounds is LIVE. @MarkPochapin, @DrHLofton & @KHochmanMD are talking with @dpedelson@UChicagoMed Call us at 877-698-3627. https://t.co/vuGRUcZrG6
We are proud to announce that eCART has received #FDA clearance to support frontline teams in identifying the highest-risk hospitalized patients. We are grateful for the opportunity and excited to make an even bigger impact moving forward! Learn more here: https://t.co/nP8x3JdFcl