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Paper Details

Inclusion of Unstructured Clinical Text Improves Early Prediction of Death or Prolonged ICU Stay.
Crit Care Med
43
2018
PATIENTS, patient, patients, text-derived variables
Aged, Decision Support Techniques, Female, Hospital Mortality, Humans, Intensive Care Units, Length of Stay, Machine Learning, Male, Middle Aged, Natural Language Processing, Patient Care Planning, Retrospective Studies
Author NameAffiliation
Gary E WeissmanPerelman School of Medicine, University of Pennsylvania
Gary E WeissmanPalliative and Advanced Illness Research Center, Perelman School of Medicine, University of Pennsylvania
Gary E WeissmanLeonard Davis Institute of Health Economics, University of Pennsylvania
Rebecca A HubbardPerelman School of Medicine, University of Pennsylvania
Lyle H UngarUniversity of Pennsylvania
Michael O HarhayPalliative and Advanced Illness Research Center, Perelman School of Medicine, University of Pennsylvania
Michael O HarhayPerelman School of Medicine, University of Pennsylvania
Casey S GreeneUniversity of Pennsylvania
Casey S GreeneInstitute for Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania
Casey S GreeneInstitute for Biomedical Informatics, Perelman School of Medicine, University of Pennsylvania
Blanca E HimesPerelman School of Medicine, University of Pennsylvania
Blanca E HimesInstitute for Biomedical Informatics, Perelman School of Medicine, University of Pennsylvania
Scott D HalpernPerelman School of Medicine, University of Pennsylvania
Scott D HalpernPalliative and Advanced Illness Research Center, Perelman School of Medicine, University of Pennsylvania
Scott D HalpernLeonard Davis Institute of Health Economics, University of Pennsylvania
Scott D HalpernPerelman School of Medicine, University of Pennsylvania
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