Machine learning interpretability methods to characterize the importance of hematologic biomarkers in prognosticating patients with suspected infection.

Journal: Computers in biology and medicine
Published Date: Oct 12, 2024

Abstract

OBJECTIVE: To evaluate the effectiveness of Monocyte Distribution Width (MDW) in predicting sepsis outcomes in emergency department (ED) patients compared to other hematologic parameters and vital signs, and to determine whether routine parameters could substitute MDW in machine learning models.

Authors

  • Dipak P Upadhyaya
    Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH, USA.
  • Yasir Tarabichi
    Department of Population and Quantitative Health Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, USA; Center for Clinical Informatics Research and Education, MetroHealth System, Cleveland, OH, USA.
  • Katrina Prantzalos
    Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH, USA.
  • Salman Ayub
    Center for Clinical Informatics Research and Education, MetroHealth System, Cleveland, OH, USA.
  • David C Kaelber
    Center for Clinical Informatics Research and Education, The Metro Health System, Cleveland, OH, USA.
  • Satya S Sahoo
    Division of Medical Informatics, School of Medicine, Case Western Reserve University, Cleveland, OH.

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