Opportunities and Challenges of Large Language Models in Medical Imaging

Ali  Tarighatnia; Masoud  Amanzadeh; Mahnaz  Hamedan; Mahnaz  Kiani; Nader D.  Nader

doi:10.18502/fbt.v12i2.18267

Ali Tarighatnia Department of Medical Physics, School of Medicine, Ardabil University of Medical Sciences, Ardabil, Iran
Masoud Amanzadeh Department of Health Information Management, School of Medicine, Ardabil University of Medical Sciences, Ardabil, Iran
Mahnaz Hamedan Department of Health Information Management, School of Medicine, Ardabil University of Medical Sciences, Ardabil, Iran
Mahnaz Kiani Research Center for Molecular and Cellular Imaging, Tehran University of Medical Sciences, Tehran, Iran
Nader D. Nader Department of Anesthesiology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, Buffalo, NY, USA

DOI: https://doi.org/10.18502/fbt.v12i2.18267

Keywords: Large Language Models; Medical Imaging; Opportunities; Challenges.

Abstract

Large Language Models (LLMs) have the potential to revolutionize medical imaging by improving diagnostic accuracy, enhancing workflow efficiency, and advancing personalized medicine. However, addressing the challenges related to data privacy, hallucinations, interpretability, bias, and regulatory issues is crucial for the successful and ethical integration of LLMs into clinical practice. Collaboration between radiologists, AI developers, and other stakeholders is essential to ensure this technology benefits patients and healthcare providers.