Challenging cases of hyponatremia incorrectly interpreted by ChatGPT.

Journal: BMC medical education
Published Date:

Abstract

BACKGROUND: In clinical medicine, the assessment of hyponatremia is frequently required but also known as a source of major diagnostic errors, substantial mismanagement, and iatrogenic morbidity. Because artificial intelligence techniques are efficient in analyzing complex problems, their use may possibly overcome current assessment limitations. There is no literature concerning Chat Generative Pre-trained Transformer (ChatGPT-3.5) use for evaluating difficult hyponatremia cases. Because of the interesting pathophysiology, hyponatremia cases are often used in medical education for students to evaluate patients with students increasingly using artificial intelligence as a diagnostic tool. To evaluate this possibility, four challenging hyponatremia cases published previously, were presented to the free ChatGPT-3.5 for diagnosis and treatment suggestions.

Authors

  • Kenrick Berend
    Department of Medicine, Curaçao Medical Center, Willemstad, Curaçao. kenber2@me.com.
  • Ashley Duits
    Institute for Medical Education, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.
  • Reinold O B Gans
    Department of Medicine, Curaçao Medical Center, Willemstad, Curaçao.