PEER-REVIEWED PUBLICATIONS

Papers and abstracts

Artificial Intelligence Occult Sepsis Detection in the Emergency Department: A Large, Multicenter Real-World Data Study

Annals of Emergency Medicine, 78 (4), S24, 2021. Plenary session abstract presented at ACEP21.

In collaboration with one of the global leaders in acute care biomarkers, Dr. Frank Peacock, we have demonstrated the ability to go beyond traditional alerts and showed how our AI can detect sepsis many hours before it satisfies traditional clinical criteria ("occult sepsis").

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Development and External Validation of a Machine Learning Tool to Rule Out COVID-19 Among Adults in the Emergency Department Using Routine Blood Tests: A Large, Multicenter, Real-World Study

JMIR 2020;22(12):e24048

In this study that included a large number of sites and patient encounters, we describe a model that can discriminate COVID-19 using only routine blood tests, and that generalizes well to hospitals other than the ones it was trained on.

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Other papers by our team