Applications of Artificial Intelligence in the Radiology Roundtrip: Process Streamlining, Workflow Optimization, and Beyond.

Journal: Seminars in roentgenology
Published Date: Mar 23, 2023

Abstract

There are many impactful applications of artificial intelligence (AI) in the electronic radiology roundtrip and the patient's journey through the healthcare system that go beyond diagnostic applications. These tools have the potential to improve quality and safety, optimize workflow, increase efficiency, and increase patient satisfaction. In this article, we review the role of AI for process improvement and workflow enhancement which includes applications beginning from the time of order entry, scan acquisition, applications supporting the image interpretation task, and applications supporting tasks after image interpretation such as result communication. These non-diagnostic workflow and process optimization tasks are an important part of the arsenal of potential AI tools that can streamline day to day clinical practice and patient care.

Authors

  • Kevin Pierre
    Radiomics and Augmented Intelligence Laboratory (RAIL), Department of Radiology and the Norman Fixel Institute for Neurological Diseases, University of Florida College of Medicine, Gainesville, FL; Department of Radiology, University of Florida College of Medicine, Gainesville, FL.
  • Adam G Haneberg
    Radiomics and Augmented Intelligence Laboratory (RAIL), Department of Radiology and the Norman Fixel Institute for Neurological Diseases, University of Florida College of Medicine, Gainesville, FL; Division of Medical Physics, Department of Radiology, University of Florida College of Medicine, Gainesville, FL.
  • Sean Kwak
    Radiomics and Augmented Intelligence Laboratory (RAIL), Department of Radiology and the Norman Fixel Institute for Neurological Diseases, University of Florida College of Medicine, Gainesville, FL.
  • Keith R Peters
    Radiomics and Augmented Intelligence Laboratory (RAIL), Department of Radiology and the Norman Fixel Institute for Neurological Diseases, University of Florida College of Medicine, Gainesville, FL; Department of Radiology, University of Florida College of Medicine, Gainesville, FL.
  • Bruno Hochhegger
    Pontificia Universidade Catolica do Rio Grande do Sul.
  • Thiparom Sananmuang
    Department of Diagnostic and Therapeutic Radiology and Research, Faculty of Medicine Ramathibodi Hospital, Ratchathewi, Bangkok 10400, Thailand.
  • Padcha Tunlayadechanont
    Department of Diagnostic and Therapeutic Radiology and Research, Faculty of Medicine Ramathibodi Hospital, Ratchathewi, Bangkok, Thailand.
  • Patrick J Tighe
    Department of Anesthesiology, University of Florida College of Medicine, Gainesville, Florida, USA.
  • Anthony Mancuso
    Department of Radiology, University of Florida College of Medicine, Gainesville, Florida.
  • Reza Forghani
    Department of Radiology, McGill University Health Centre, 1001 Decarie Blvd, Room C02.5821, Montreal, QC, Canada H4A 3J1; Augmented Intelligence & Precision Health Laboratory (AIPHL), Research Institute of the McGill University Health Centre, Montreal, Canada; Segal Cancer Centre and Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal, Canada; Gerald Bronfman Department of Oncology, McGill University, Montreal, Canada; and Department of Otolaryngology-Head and Neck Surgery, McGill University, Montreal, Canada.

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