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

Opportunities and Challenges of Large Language Models in Medical Imaging

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

Department of Anesthesiology

University at Buffalo

Ardabil University of Medical Sciences
Tehran University of Medical Sciences

Research output: Contribution to journal › Review article › peer-review

2 Scopus citations

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.

Original language	English
Pages (from-to)	205-209
Number of pages	5
Journal	Frontiers in Biomedical Technologies
Volume	12
Issue number	2
DOIs	https://doi.org/10.18502/fbt.v12i2.18267
State	Published - 2025

Keywords

Challenges
Large Language Models
Medical Imaging
Opportunities

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10.18502/fbt.v12i2.18267

Cite this

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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.",

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AU - Tarighatnia, Ali

AU - Amanzadeh, Masoud

AU - Hamedan, Mahnaz

AU - Kiani, Mahnaz

AU - Nader, Nader D.

PY - 2025

Y1 - 2025

N2 - 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.

AB - 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.

KW - Challenges

KW - Large Language Models

KW - Medical Imaging

KW - Opportunities

UR - https://www.scopus.com/pages/publications/105008279272

U2 - 10.18502/fbt.v12i2.18267

DO - 10.18502/fbt.v12i2.18267

M3 - Review article

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SP - 205

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JO - Frontiers in Biomedical Technologies

JF - Frontiers in Biomedical Technologies

IS - 2

ER -

Opportunities and Challenges of Large Language Models in Medical Imaging

Abstract

Keywords

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