Building artificial intelligence and machine learning models : a primer for emergency physicians.

Journal: Emergency medicine journal : EMJ
Published Date: Mar 3, 2022

Abstract

There has been a rise in the number of studies relating to the role of artificial intelligence (AI) in healthcare. Its potential in Emergency Medicine (EM) has been explored in recent years with operational, predictive, diagnostic and prognostic emergency department (ED) implementations being developed. For EM researchers building models de novo, collaborative working with data scientists is invaluable throughout the process. Synergism and understanding between domain (EM) and data experts increases the likelihood of realising a successful real-world model. Our linked manuscript provided a conceptual framework (including a glossary of AI terms) to support clinicians in interpreting AI research. The aim of this paper is to supplement that framework by exploring the key issues for clinicians and researchers to consider in the process of developing an AI model.

Authors

  • Shammi L Ramlakhan
    Emergency Department, Sheffield Children's NHS Foundation Trust, Sheffield, UK sramlakhan@nhs.net.
  • Reza Saatchi
    Materials and Engineering Research Institute, Sheffield Hallam University, Sheffield, UK.
  • Lisa Sabir
    Emergency Department, Sheffield Children's Hospital, Sheffield, UK.
  • Dale Ventour
    Department of Clinical Surgical Sciences, Faculty of Medical Sciences, The University of the West Indies, St Augustine, Trinidad and Tobago.
  • Olamilekan Shobayo
    Electronics and Computer Engineering Research Institute, Sheffield Hallam University, Sheffield, UK.
  • Ruby Hughes
    Simulation and Modelling Unit, Advanced Forming Research Centre, University of Strathclyde, Sheffield, UK.
  • Yardesh Singh
    Department of Clinical Surgical Sciences, Faculty of Medical Sciences, The University of the West Indies, St Augustine, Trinidad and Tobago.

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