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Generative artificial intelligence (genAI) offers potential benefits for nuclear medicine education and sustainability. While current genAI tools are not revolutionary, they can enhance student learning and provide economies in education and clinical sectors.

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Area of Science:

  • Nuclear Medicine
  • Artificial Intelligence
  • Health Care Education

Background:

  • Generative artificial intelligence (genAI) is increasingly integrated into nuclear medicine and healthcare.
  • Understanding genAI's principles and limitations is crucial for its effective application.

Purpose of the Study:

  • To explore fundamental principles and applications of artificial intelligence in nuclear medicine.
  • To define genAI technologies and outline their capabilities.
  • To investigate the potential and limitations of text-to-text and text-to-image genAI.

Main Methods:

  • Review of empirical and anecdotal research on genAI.
  • Exploration of fundamental AI principles within nuclear medicine.
  • Definition and outlining of genAI capabilities.

Main Results:

  • GenAI has the potential to enhance nuclear medicine education and student learning.
  • Text-to-text and text-to-image genAI applications are explored with examples.
  • Current genAI capabilities are not yet revolutionary but show future promise.

Conclusions:

  • GenAI can invigorate nuclear medicine education and improve sustainability in education and clinical sectors.
  • Despite current limitations, genAI offers significant future benefits for education.
  • The rapid evolution of genAI suggests transformative potential for the field.