USE OF CHATGPT-3 BY ON-CALL RADIOLOGY RESIDENTS AND CONSULTANTS

Abstract

Abstract

Objective: This study explores the utilization and impact of ChatGPT-3, a state-of-the-art AI language model, among on-call radiology residents and experienced radiology consultants. The objective is to understand how ChatGPT-3 influences clinical practice, communication, and patient care within the dynamic and time-sensitive realm of radiology.

Methods: A mixed-methods approach was employed, combining surveys and in-depth interviews with radiology residents and consultants across various healthcare institutions. The participants provided information about their experience with ChatGPT-3, including its frequency of use, purposes, perceived advantages, and limitations. Qualitative data were analyzed thematically, and quantitative data were subjected to descriptive statistical analysis.

Results: The findings demonstrate that ChatGPT-3 has become an integral tool for on-call radiology professionals, aiding in image interpretation, report generation, and access to up-to-date medical literature. Participants reported that ChatGPT-3 enhanced the speed and accuracy of their radiological assessments, particularly in complex and time-sensitive cases. Moreover, it facilitated seamless communication with colleagues, including referring physicians, and improved the overall quality of patient care. However, challenges such as concerns over data privacy and occasional inaccuracies in responses were noted.

Conclusion: ChatGPT-3 is increasingly becoming a valuable asset for on-call radiology residents and consultants, transforming radiological practice by accelerating decision-making, enhancing collaboration, and improving patient outcomes. Despite some limitations, the technology's role in radiology appears promising, suggesting a need for further research and guidelines to optimize its integration and ensure patient data security.

Keywords: ChatGPT-3, radiology, on-call, AI, communication, patient care, medical imaging.