INNOVATION
Transforming Emergency Medicine: Highlights From an Expert Panel on AI and Machine Learning
SAEM PULSE | JULY-AUGUST 2023
By Kirsten Douglass, MD, Nicholas Stark, MD, MBA, Jonathan Oskvarek, MD, MBA, and Zaid Altawil, MD on behalf of the SAEM Innovation Interest Group
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Artificial intelligence (AI) and machine learning (ML) have emerged as powerful tools in transforming emergency medicine. These technologies offer promising applications that enhance decision-making, improve patient outcomes, and optimize resource allocation. In the realm of triage, AI algorithms can analyze patient data such as vital signs, symptoms, and medical history to accurately prioritize cases based on urgency. Machine learning models trained on large datasets enable the early identification of critical conditions, such as sepsis, by recognizing patterns and alerting
medical staff. AI-powered imaging analysis plays a vital role in radiology, assisting in the rapid detection of abnormalities in images, thereby expediting diagnosis and treatment. That introduction sounds pretty good, right? In full disclosure: the above paragraph was generated by ChatGPT when prompted to “write a paragraph about artificial intelligence and machine learning applications in emergency medicine.” At SAEM23 in Austin, Texas, the SAEM Innovation Interest Group partnered with the SAEM Informatics
& Data Science Interest Group and the Emergency Medicine Innovation Collaborative to host a panel titled “Innovating in Acute Care: Artificial Intelligence and Machine Learning.” Throughout the discussion, two emergency physicians on the cutting edge of artificial intelligence and machine learning — Drs. Christian Rose and David Kim, both of Stanford Emergency Medicine — explored the current and potential future applications of these technologies. What follows is an explorative summary of their discussion.