The first use of artificial intelligence (AI) in the ER: triage not diagnosis.

Journal: Emergency radiology
Published Date:

Abstract

Predictions related to the impact of AI on radiology as a profession run the gamut from AI putting radiologists out of business to having no effect at all. The use of AI appears to show significant promise in ER triage in the present. We briefly discuss the emerging effectiveness of AI in the ER imaging setting by looking at some of the products approved by the FDA and finding their way into "practice." The FDA approval process to date has focused on applications that affect patient triage and not necessarily ones that have the computer serve as the only or final reader. We describe a select group of applications to provide the reader with a sense of the current state of AI use in the ER setting to assess neurologic, pulmonary, and musculoskeletal trauma indications. In the process, we highlight the benefits of triage staging using AI, such as accelerating diagnosis and optimizing workflow, with few downsides. The ability to triage patients and take care of acute processes such as intracranial bleed, pneumothorax, and pulmonary embolism will largely benefit the health system, improving patient care and reducing costs. These capabilities are all available now. This first wave of AI applications is not replacing radiologists. Rather, the innovative software is improving throughput, contributing to the timeliness in which radiologists can get to read abnormal scans, and possibly enhances radiologists' accuracy. As for what the future holds for the use of AI in radiology, only time will tell.

Authors

  • Edmund M Weisberg
    Professor, Johns Hopkins Medicine, Department of Radiology and Radiological Science, Department of Oncology and Department of Surgery; Director of Diagnostic Imaging and Body CT at Johns Hopkins University School of Medicine, Baltimore, Maryland; Senior Science Writer, The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins Hospital, Baltimore, Maryland; The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins Hospital, Baltimore, Maryland. Electronic address: eweisbe1@jhmi.edu.
  • Linda C Chu
    The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland. Electronic address: lindachu@jhmi.edu.
  • Elliot K Fishman
    The Russell H. Morgan Department of Radiology and Radiologic Science, Johns Hopkins School of Medicine, Baltimore, Maryland. Electronic address: efishman@jhmi.edu.