A recent review published in Radiology outlines essential guidelines for integrating large language models (LLMs) in radiology, focusing on regulatory oversight, data privacy, and bias reduction. The review emphasizes the importance of these factors for safe clinical use and suggests that current regulatory frameworks, such as those from the FDA and EU AI Act, need to evolve. It highlights the potential of LLMs to generate accurate radiology reports, but also points out challenges like performance variability, data handling risks, and biases in model outputs. Researchers propose strategies to mitigate these issues, including local deployment of models, diverse dataset inclusion, and ongoing bias testing. The lead researcher, Dr. Paul H. Yi, stresses the need for vigilance in addressing these pitfalls to ensure equitable patient care.
Wed, 15 Oct 2025 15:35:57 GMT | Conexiant