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Radiology Gets Chatty: The ChatGPT Saga Unfolds
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 Transform...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cureus
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10329466/ https://www.ncbi.nlm.nih.gov/pubmed/37425598 http://dx.doi.org/10.7759/cureus.40135 |
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author | Grewal, Harpreet Dhillon, Gagandeep Monga, Varun Sharma, Pranjal Buddhavarapu, Venkata S Sidhu, Gurmanpreet Kashyap, Rahul |
author_facet | Grewal, Harpreet Dhillon, Gagandeep Monga, Varun Sharma, Pranjal Buddhavarapu, Venkata S Sidhu, Gurmanpreet Kashyap, Rahul |
author_sort | Grewal, Harpreet |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-10329466 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Cureus |
record_format | MEDLINE/PubMed |
spelling | pubmed-103294662023-07-09 Radiology Gets Chatty: The ChatGPT Saga Unfolds Grewal, Harpreet Dhillon, Gagandeep Monga, Varun Sharma, Pranjal Buddhavarapu, Venkata S Sidhu, Gurmanpreet Kashyap, Rahul Cureus Radiology 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. Cureus 2023-06-08 /pmc/articles/PMC10329466/ /pubmed/37425598 http://dx.doi.org/10.7759/cureus.40135 Text en Copyright © 2023, Grewal et al. https://creativecommons.org/licenses/by/3.0/This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Radiology Grewal, Harpreet Dhillon, Gagandeep Monga, Varun Sharma, Pranjal Buddhavarapu, Venkata S Sidhu, Gurmanpreet Kashyap, Rahul Radiology Gets Chatty: The ChatGPT Saga Unfolds |
title | Radiology Gets Chatty: The ChatGPT Saga Unfolds |
title_full | Radiology Gets Chatty: The ChatGPT Saga Unfolds |
title_fullStr | Radiology Gets Chatty: The ChatGPT Saga Unfolds |
title_full_unstemmed | Radiology Gets Chatty: The ChatGPT Saga Unfolds |
title_short | Radiology Gets Chatty: The ChatGPT Saga Unfolds |
title_sort | radiology gets chatty: the chatgpt saga unfolds |
topic | Radiology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10329466/ https://www.ncbi.nlm.nih.gov/pubmed/37425598 http://dx.doi.org/10.7759/cureus.40135 |
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