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Applications of large language models in cancer care: current evidence and future perspectives

The development of large language models (LLMs) is a recent success in the field of generative artificial intelligence (AI). They are computer models able to perform a wide range of natural language processing tasks, including content generation, question answering, or language translation. In recen...

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Autores principales: Iannantuono, Giovanni Maria, Bracken-Clarke, Dara, Floudas, Charalampos S., Roselli, Mario, Gulley, James L., Karzai, Fatima
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10507617/
https://www.ncbi.nlm.nih.gov/pubmed/37731643
http://dx.doi.org/10.3389/fonc.2023.1268915
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author Iannantuono, Giovanni Maria
Bracken-Clarke, Dara
Floudas, Charalampos S.
Roselli, Mario
Gulley, James L.
Karzai, Fatima
author_facet Iannantuono, Giovanni Maria
Bracken-Clarke, Dara
Floudas, Charalampos S.
Roselli, Mario
Gulley, James L.
Karzai, Fatima
author_sort Iannantuono, Giovanni Maria
collection PubMed
description The development of large language models (LLMs) is a recent success in the field of generative artificial intelligence (AI). They are computer models able to perform a wide range of natural language processing tasks, including content generation, question answering, or language translation. In recent months, a growing number of studies aimed to assess their potential applications in the field of medicine, including cancer care. In this mini review, we described the present published evidence for using LLMs in oncology. All the available studies assessed ChatGPT, an advanced language model developed by OpenAI, alone or compared to other LLMs, such as Google Bard, Chatsonic, and Perplexity. Although ChatGPT could provide adequate information on the screening or the management of specific solid tumors, it also demonstrated a significant error rate and a tendency toward providing obsolete data. Therefore, an accurate, expert-driven verification process remains mandatory to avoid the potential for misinformation and incorrect evidence. Overall, although this new generative AI-based technology has the potential to revolutionize the field of medicine, including that of cancer care, it will be necessary to develop rules to guide the application of these tools to maximize benefits and minimize risks.
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spelling pubmed-105076172023-09-20 Applications of large language models in cancer care: current evidence and future perspectives Iannantuono, Giovanni Maria Bracken-Clarke, Dara Floudas, Charalampos S. Roselli, Mario Gulley, James L. Karzai, Fatima Front Oncol Oncology The development of large language models (LLMs) is a recent success in the field of generative artificial intelligence (AI). They are computer models able to perform a wide range of natural language processing tasks, including content generation, question answering, or language translation. In recent months, a growing number of studies aimed to assess their potential applications in the field of medicine, including cancer care. In this mini review, we described the present published evidence for using LLMs in oncology. All the available studies assessed ChatGPT, an advanced language model developed by OpenAI, alone or compared to other LLMs, such as Google Bard, Chatsonic, and Perplexity. Although ChatGPT could provide adequate information on the screening or the management of specific solid tumors, it also demonstrated a significant error rate and a tendency toward providing obsolete data. Therefore, an accurate, expert-driven verification process remains mandatory to avoid the potential for misinformation and incorrect evidence. Overall, although this new generative AI-based technology has the potential to revolutionize the field of medicine, including that of cancer care, it will be necessary to develop rules to guide the application of these tools to maximize benefits and minimize risks. Frontiers Media S.A. 2023-09-04 /pmc/articles/PMC10507617/ /pubmed/37731643 http://dx.doi.org/10.3389/fonc.2023.1268915 Text en Copyright © 2023 Iannantuono, Bracken-Clarke, Floudas, Roselli, Gulley and Karzai https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Oncology
Iannantuono, Giovanni Maria
Bracken-Clarke, Dara
Floudas, Charalampos S.
Roselli, Mario
Gulley, James L.
Karzai, Fatima
Applications of large language models in cancer care: current evidence and future perspectives
title Applications of large language models in cancer care: current evidence and future perspectives
title_full Applications of large language models in cancer care: current evidence and future perspectives
title_fullStr Applications of large language models in cancer care: current evidence and future perspectives
title_full_unstemmed Applications of large language models in cancer care: current evidence and future perspectives
title_short Applications of large language models in cancer care: current evidence and future perspectives
title_sort applications of large language models in cancer care: current evidence and future perspectives
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10507617/
https://www.ncbi.nlm.nih.gov/pubmed/37731643
http://dx.doi.org/10.3389/fonc.2023.1268915
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