Machine learning-driven prediction of hospital admissions using gradient boosting and GPT-2.

Journal: Digital health
Published Date: Mar 28, 2025

Abstract

BACKGROUND: Accurately predicting hospital admissions from the emergency department (ED) is essential for improving patient care and resource allocation. This study aimed to predict hospital admissions by integrating both structured clinical data and unstructured text data using machine learning models.

Authors

  • Xingyu Zhang
    Department of Communication Science and Disorders, School of Health and Rehabilitation Sciences, University of Pittsburgh, Pittsburgh, PA, USA.
  • Hairong Wang
    College of Computing, Georgia Institute of Technology, Atlanta, GA, USA.
  • Guan Yu
    Department of Biostatistics and Health Data Science, School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA.
  • Wenbin Zhang
    Department of Epidemiology and Medical Statistics School of Public Health, Guangdong Medical University, Dongguan, Guangdong, China.

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