Bibliographic Details
| Title: |
Applications of large language models in cancer care: current evidence and future perspectives |
| Authors: |
Giovanni Maria Iannantuono, Dara Bracken-Clarke, Charalampos S. Floudas, Mario Roselli, James L. Gulley, Fatima Karzai |
| Source: |
Frontiers in Oncology, Vol 13 (2023) |
| Publisher Information: |
Frontiers Media S.A., 2023. |
| Publication Year: |
2023 |
| Collection: |
LCC:Neoplasms. Tumors. Oncology. Including cancer and carcinogens |
| Subject Terms: |
artificial intelligence, large language models, chatbot, cancer care, ChatGPT, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282 |
| More Details: |
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. |
| Document Type: |
article |
| File Description: |
electronic resource |
| Language: |
English |
| ISSN: |
2234-943X |
| Relation: |
https://www.frontiersin.org/articles/10.3389/fonc.2023.1268915/full; https://doaj.org/toc/2234-943X |
| DOI: |
10.3389/fonc.2023.1268915 |
| Access URL: |
https://doaj.org/article/6a3c519940f54eab87d348289a43f5e8 |
| Accession Number: |
edsdoj.6a3c519940f54eab87d348289a43f5e8 |
| Database: |
Directory of Open Access Journals |
