Prediction of Clinical Deterioration in Hospitalized Adult Patients with Hematologic Malignancies Using a Neural Network Model.

Journal: PloS one
Published Date: Jan 1, 2016

Abstract

INTRODUCTION: Clinical deterioration (ICU transfer and cardiac arrest) occurs during approximately 5-10% of hospital admissions. Existing prediction models have a high false positive rate, leading to multiple false alarms and alarm fatigue. We used routine vital signs and laboratory values obtained from the electronic medical record (EMR) along with a machine learning algorithm called a neural network to develop a prediction model that would increase the predictive accuracy and decrease false alarm rates.

Authors

  • Scott B Hu
    Division of Pulmonary/Critical Care, University of California, Los Angeles, Los Angeles, California, United States of America.
  • Deborah J L Wong
    Division of Hematology/Oncology, University of California, Los Angeles, Los Angeles, California, United States of America.
  • Aditi Correa
    Downstate College of Medicine, State University of New York, Albany, New York, United States of America.
  • Ning Li
    Department of Respiratory and Critical Care Medicine, Center for Respiratory Medicine, the Fourth Affiliated Hospital of School of Medicine, and International School of Medicine, International Institutes of Medicine, Zhejiang University, Yiwu, China.
  • Jane C Deng
    Division of Pulmonary/Critical Care, University of California, Los Angeles, Los Angeles, California, United States of America.

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