Using Automated Machine Learning to Predict the Mortality of Patients With COVID-19: Prediction Model Development Study.

Journal: Journal of medical Internet research
Published Date: Feb 26, 2021

Abstract

BACKGROUND: During a pandemic, it is important for clinicians to stratify patients and decide who receives limited medical resources. Machine learning models have been proposed to accurately predict COVID-19 disease severity. Previous studies have typically tested only one machine learning algorithm and limited performance evaluation to area under the curve analysis. To obtain the best results possible, it may be important to test different machine learning algorithms to find the best prediction model.

Authors

  • Kenji Ikemura
    Department of Pathology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
  • Eran Bellin
    Department of Epidemiology and Population Health and Medicine, Albert Einstein College of Medicine, Montefiore Medical Center, The Bronx, NY, United States.
  • Yukako Yagi
    Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, USA.
  • Henny Billett
    Department of Oncology and Medicine, Albert Einstein College of Medicine, Montefiore Medical Center, The Bronx, NY, United States.
  • Mahmoud Saada
    Tsubomi Technology, The Bronx, NY, United States.
  • Katelyn Simone
    Tsubomi Technology, The Bronx, NY, United States.
  • Lindsay Stahl
    Department of Epidemiology and Population Health and Medicine, Albert Einstein College of Medicine, Montefiore Medical Center, The Bronx, NY, United States.
  • James Szymanski
    Department of Pathology, Albert Einstein College of Medicine, Montefiore Medical Center, The Bronx, NY, United States.
  • D Y Goldstein
    Department of Pathology, Albert Einstein College of Medicine, Montefiore Medical Center, The Bronx, NY, United States.
  • Morayma Reyes Gil
    From the Montefiore Medical Center, Bronx, New York (D.L.L., M.R.G., D.V.); and AiCure, New York, NY (L.S., A.H.).

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