Large language models in radiology workflows: An exploratory study of generative AI for non-visual tasks in the German healthcare system
The integration of LLMs is hindered by regulatory challenges, outdated infrastructure, and limited awareness among radiologists. Policymakers should establish clear, practical regulations to address liability and ethical concerns while ensuring compliance with privacy standards. Investments in modernizing clinical infrastructure and expanding training programs are critical to enable radiologists to effectively use these tools. By addressing these barriers, LLMs can enhance efficiency, reduce workloads, and improve patient care, while preserving the central role of radiologists in diagnostic and therapeutic processes.
Authors
- Stefanie Steinhauser (ORCID: https://orcid.org/0000-0002-4127-736X)
- Sabrina Welsch
Institutions
- OTH Regensburg (DE)
- Ostbayerische Technische Hochschule Amberg-Weiden (DE)
Publication Details
- Journal
- Health Policy
- Published
- 2025-09-16
- DOI
- https://doi.org/10.1016/j.healthpol.2025.105444
- Citations
- 1
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.65