Confidence-based laboratory test reduction recommendation algorithm.

Journal: BMC medical informatics and decision making
Published Date: May 10, 2023

Abstract

BACKGROUND: We propose a new deep learning model to identify unnecessary hemoglobin (Hgb) tests for patients admitted to the hospital, which can help reduce health risks and healthcare costs.

Authors

  • Tongtong Huang
    School of Biomedical Informatics, The University of Texas Health Science Center at Houston.
  • Linda T Li
    Department of Pediatric Surgery; McGovern Medical School at The University of Texas Health Science Center at Houston. Electronic address: Linda.T.Li@uth.tmc.edu.
  • Elmer V Bernstam
    Center for Computational Biomedicine, School of Biomedical Informatics, University of Texas Health Science Center at Houston, Houston, TX 77030, USA, Department of Public Health Science, Medical University of South Carolina, 135 Cannon Street, Suite 303, Charleston, SC 29425, USA and Department of Investigational Cancer Therapeutics, Institute for Personalized Cancer Therapy, UT-MD Anderson Cancer Center, 1400 Holcombe Blvd., FC8.3044, Houston, TX 77030, USA.
  • Xiaoqian Jiang
    School of Biomedical Informatics, University of Texas Health, Science Center at Houston, Houston, TX, USA.

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