Human intention recognition for trauma resuscitation: An interpretable deep learning approach for medical process data.

Journal: Journal of biomedical informatics
PMID: 39746431

Abstract

OBJECTIVE: Trauma resuscitation is the initial evaluation and management of injured patients in the emergency department. This time-critical process requires the simultaneous pursuit of multiple resuscitation goals. Recognizing whether the required goal is being pursued can reduce errors in goal-related task performance and improve patient outcomes. The intention to pursue a goal can often be inferred from ongoing and completed treatment activities, but monitoring goal pursuit is cognitively demanding and prone to errors. We introduced an interpretable deep learning-based approach to aid decision making by automatically recognizing goal pursuit during trauma resuscitation.

Authors

  • Keyi Li
    Department of Electrical and Computer Engineering, Rutgers University, Piscataway, NJ, USA. Electronic address: kl734@scarletmail.rutgers.edu.
  • Mary S Kim
    Division of Trauma and Burn Surgery, Children's National Hospital, Washington, DC, USA. Electronic address: mskim@childrensnational.org.
  • Wenjin Zhang
    Department of Biochemistry and Molecular & Cellular Biology, Georgetown University, Washington, DC 20007, USA.
  • Sen Yang
    Key Laboratory of Symbol Computation and Knowledge Engineering of Ministry of Education, College of Computer Science and Technology, Jilin University, Changchun, 130012, China.
  • Genevieve J Sippel
    Division of Trauma and Burn Surgery, Children's National Hospital, Washington, DC, USA. Electronic address: jayne.sippel18@gmail.com.
  • Aleksandra Sarcevic
    College of Computing and Informatics, Drexel University, Philadelphia, PA, USA. Electronic address: as3653@drexel.edu.
  • Randall S Burd
    Division of Trauma and Burn Surgery, Children's National Hospital, Washington, DC, USA. Electronic address: rburd@childrensnational.org.
  • Ivan Marsic
    Department of Electrical and Computer Engineering, Rutgers University, Piscataway, NJ, USA. Electronic address: marsic@rutgers.edu.

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