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Paper Details

Applying Artificial Intelligence to Identify Physiomarkers Predicting Severe Sepsis in the PICU.
Pediatr Crit Care Med
69
2018
Children, PATIENTS, Severe Sepsis, children, critically, critically ill, patients, sepsis, severe sepsis
Adolescent, Artificial Intelligence, Case-Control Studies, Child, Female, Heart Rate, Humans, Intensive Care Units, Pediatric, Logistic Models, Machine Learning, Male, Monitoring, Physiologic, Organ Dysfunction Scores, Predictive Value of Tests, Prospective Studies, Respiratory Rate, Sepsis
Author NameAffiliation
Rishikesan KamaleswaranCenter for Biomedical Informatics, University of Tennessee Health Science Center
Rishikesan KamaleswaranUniversity of Tennessee Health Science Center
Oguz AkbilgicCenter for Biomedical Informatics, University of Tennessee Health Science Center
Madhura A HallmanUniversity of Tennessee Health Science Center
Alina N WestUniversity of Tennessee Health Science Center
Robert L DavisCenter for Biomedical Informatics, University of Tennessee Health Science Center
Samir ShahUniversity of Tennessee Health Science Center
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