Evaluating a large language model's accuracy in chest X-ray interpretation for acute thoracic conditions.

Journal: The American journal of emergency medicine
Published Date:

Abstract

BACKGROUND: The rapid advancement of artificial intelligence (AI) has great ability to impact healthcare. Chest X-rays are essential for diagnosing acute thoracic conditions in the emergency department (ED), but interpretation delays due to radiologist availability can impact clinical decision-making. AI models, including deep learning algorithms, have been explored for diagnostic support, but the potential of large language models (LLMs) in emergency radiology remains largely unexamined.

Authors

  • Adam M Ostrovsky
    Sidney Kimmel Medical College at Thomas Jefferson University, Philadelphia, PA, USA. Electronic address: Adam.ostrovsky@students.jefferson.edu.