The Clinicians’ Guide to Large Language Models: A General Perspective With a Focus on Hallucinations
Large language models (LLMs) are artificial intelligence tools that have the prospect of profoundly changing how we practice all aspects of medicine. Considering the incredible potential of LLMs in medicine and the interest of many health care stakeholders for implementation into routine...
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| Format: | Article |
| Language: | English |
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JMIR Publications
2025-01-01
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| Series: | Interactive Journal of Medical Research |
| Online Access: | https://www.i-jmr.org/2025/1/e59823 |
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| author | Dimitri Roustan François Bastardot |
| author_facet | Dimitri Roustan François Bastardot |
| author_sort | Dimitri Roustan |
| collection | DOAJ |
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Large language models (LLMs) are artificial intelligence tools that have the prospect of profoundly changing how we practice all aspects of medicine. Considering the incredible potential of LLMs in medicine and the interest of many health care stakeholders for implementation into routine practice, it is therefore essential that clinicians be aware of the basic risks associated with the use of these models. Namely, a significant risk associated with the use of LLMs is their potential to create hallucinations. Hallucinations (false information) generated by LLMs arise from a multitude of causes, including both factors related to the training dataset as well as their auto-regressive nature. The implications for clinical practice range from the generation of inaccurate diagnostic and therapeutic information to the reinforcement of flawed diagnostic reasoning pathways, as well as a lack of reliability if not used properly. To reduce this risk, we developed a general technical framework for approaching LLMs in general clinical practice, as well as for implementation on a larger institutional scale. |
| format | Article |
| id | doaj-art-4f912dd3aa204c96aa172b73e1b010ae |
| institution | Kabale University |
| issn | 1929-073X |
| language | English |
| publishDate | 2025-01-01 |
| publisher | JMIR Publications |
| record_format | Article |
| series | Interactive Journal of Medical Research |
| spelling | doaj-art-4f912dd3aa204c96aa172b73e1b010ae2025-01-28T19:31:07ZengJMIR PublicationsInteractive Journal of Medical Research1929-073X2025-01-0114e5982310.2196/59823The Clinicians’ Guide to Large Language Models: A General Perspective With a Focus on HallucinationsDimitri Roustanhttps://orcid.org/0009-0008-2650-4035François Bastardothttps://orcid.org/0000-0003-4060-0353 Large language models (LLMs) are artificial intelligence tools that have the prospect of profoundly changing how we practice all aspects of medicine. Considering the incredible potential of LLMs in medicine and the interest of many health care stakeholders for implementation into routine practice, it is therefore essential that clinicians be aware of the basic risks associated with the use of these models. Namely, a significant risk associated with the use of LLMs is their potential to create hallucinations. Hallucinations (false information) generated by LLMs arise from a multitude of causes, including both factors related to the training dataset as well as their auto-regressive nature. The implications for clinical practice range from the generation of inaccurate diagnostic and therapeutic information to the reinforcement of flawed diagnostic reasoning pathways, as well as a lack of reliability if not used properly. To reduce this risk, we developed a general technical framework for approaching LLMs in general clinical practice, as well as for implementation on a larger institutional scale.https://www.i-jmr.org/2025/1/e59823 |
| spellingShingle | Dimitri Roustan François Bastardot The Clinicians’ Guide to Large Language Models: A General Perspective With a Focus on Hallucinations Interactive Journal of Medical Research |
| title | The Clinicians’ Guide to Large Language Models: A General Perspective With a Focus on Hallucinations |
| title_full | The Clinicians’ Guide to Large Language Models: A General Perspective With a Focus on Hallucinations |
| title_fullStr | The Clinicians’ Guide to Large Language Models: A General Perspective With a Focus on Hallucinations |
| title_full_unstemmed | The Clinicians’ Guide to Large Language Models: A General Perspective With a Focus on Hallucinations |
| title_short | The Clinicians’ Guide to Large Language Models: A General Perspective With a Focus on Hallucinations |
| title_sort | clinicians guide to large language models a general perspective with a focus on hallucinations |
| url | https://www.i-jmr.org/2025/1/e59823 |
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