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Upcoming Webinars

Potential Use Cases for ChatGPT in Radiology Reporting

October 18, 2023

Broadcasted Live and Online 12:00 noon–1:00 pm, Eastern Time 
Moderator: AJR Section Editor McKinley Glover, MD
Speakers: Andrew D. Smith, MD, PhD, Asser Abou Elkassem, MD

Large Language Models (LLMs) such as ChatGPT offer a promising avenue for improving radiology reporting and enhancing patient engagement, as they aid radiologists in improving reporting accuracy and efficiency, reduce omissions and cognitive load, and enable the generation of layperson reports in various languages and educational levels. However, LLMs also have weaknesses and challenges, such as biases, data privacy concerns, lack of interpretability, susceptibility to adversarial attacks, and ethical considerations. To maximize the benefits of LLMs in radiology reporting, it is important to carefully plan the integration process and to validate the output generated by the LLMs, especially for complicated tasks that require abstract reasoning or contextualization of medical information.

Join AJR authors, Andrew D. Smith, MD, PhD, and Asser Abou Elkassem, MD, for a discussion of LLMs in radiology reporting. You will gain an understanding of their potential uses, strengths, and weaknesses.

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Learning Outcomes

  1. Review Large Language Models (LLMs), including Chat GPT, and their potential uses in radiology reporting.
  2. Discuss the weaknesses in LLMs for medical reporting.
  3. Describe the advantages of using LLMs in radiology reporting.

The American Roentgen Ray Society (ARRS) is accredited by the Accreditation Council for Continuing Medical Education (ACCME) to provide continuing medical education activities for physicians.

The ARRS designates this live activity for a maximum of 1.00 AMA PRA Category 1 Credit(s). Physicians should claim only the credit commensurate with the extent of their participation in the activity.