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Radiology Gets Chatty: The ChatGPT Saga Unfolds
67
Zitationen
7
Autoren
2023
Jahr
Abstract
As artificial intelligence (AI) continues to evolve and mature, it is increasingly finding applications in the field of healthcare, particularly in specialties like radiology that are data-heavy and image-focused. Language learning models (LLMs) such as OpenAI's Generative Pre-trained Transformer-4 (GPT-4) are new in the field of medicine and there is a paucity of literature regarding the possible utilities of GPT-4 given its novelty. We aim to present an in-depth exploration of the role of GPT-4, an advanced language model, in radiology. Giving the GPT-4 model prompts for generating reports, template generation, enhancing clinical decision-making, and suggesting captivating titles for research articles, patient communication, and education, can occasionally be quite generic, and at times, it may present factually incorrect content, which could lead to errors. The responses were then analyzed in detail regarding their potential utility in day-to-day radiologist workflow, patient education, and research processes. Further research is required to evaluate LLMs' accuracy and safety in clinical practice and to develop comprehensive guidelines for their implementation.
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Autoren
Institutionen
- Mayo Clinic(US)
- Remote Sensing Solutions (United States)(US)
- Government Medical College(IN)
- Mayo Clinic in Florida(US)
- Banner Health(US)
- Drexel University(US)
- University of Maryland Baltimore Washington Medical Center(US)
- Northeast Ohio Medical University(US)
- Florida State University(US)
- Harvard Global Health Institute(US)
- Mayo Clinic in Arizona(US)
- WinnMed(US)