Open AccessA Machine Learning Algorithm to Predict Severe Sepsis and Septic Shock: Development, Implementation, and Impact on Clinical Practice*
Author(s) -
H.M. Giannini,
Jennifer C Ginestra,
Corey Chivers,
Michael Draugelis,
Asaf Hanish,
William D. Schweickert,
Barry D. Fuchs,
Laurie Meadows,
Michael J. Lynch,
Patrick J. Donnelly,
Kimberly Pavan,
Neil O. Fishman,
C. William Hanson,
Craig A Umscheid
Publication year - 2019
Publication title -
critical care medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.002
H-Index - 271
eISSN - 1530-0293
pISSN - 0090-3493
DOI - 10.1097/ccm.0000000000003891
Subject(s) - medicine , septic shock , algorithm , sepsis , psychological intervention , retrospective cohort study , machine learning , random forest , clinical practice , vital signs , emergency medicine , surgery , physical therapy , computer science , psychiatry
Develop and implement a machine learning algorithm to predict severe sepsis and septic shock and evaluate the impact on clinical practice and patient outcomes.