Abstract
Large language models like ChatGPT, with their growing accessibility, are attracting increasing interest within the artificial intelligence medical field, particularly in the analysis of radiology reports. These present a valuable opportunity to explore the potential clinical applications of large language models, given their huge capabilities in processing and understanding written language. Early research indicates that ChatGPT could offer benefits in radiology reporting. ChatGPT can assist but not replace radiologists in achieving diagnoses, generating structured reports, extracting data, identifying errors or incidental findings, and can also serve as a support in creating patient-friendly reports. However, ChatGPT also has intrinsic limitations, such as hallucinations, stochasticity, biases, deficiencies in complex clinical scenarios, data privacy and legal concerns. To fully utilize the potential of ChatGPT in radiology reporting, careful integration planning and rigorous validation of their outputs are crucial, especially for tasks requiring abstract reasoning or nuanced medical context. Radiologists' expertise in medical imaging and data analysis positions them exceptionally well to lead the responsible integration and utilization of ChatGPT within the field of radiology. This article offers a topical overview of the potential strengths and limitations of ChatGPT in radiological reporting.
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