Potential Use of ChatGPT for the Treatment of Infectious Diseases in Vulnerable Populations.
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| Title: | Potential Use of ChatGPT for the Treatment of Infectious Diseases in Vulnerable Populations. |
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| Authors: | Tao, Heqing1 (AUTHOR), Liu, Ligang2 (AUTHOR), Cui, Jiayu3 (AUTHOR), Wang, Kunkun4 (AUTHOR), Peng, Liang1 (AUTHOR), Nahata, Milap C.2,5 (AUTHOR) nahata.1@osu.edu |
| Source: | Annals of Biomedical Engineering. Dec2024, Vol. 52 Issue 12, p3141-3144. 4p. |
| Subjects: | Medical personnel, ChatGPT, Communicable diseases, Juvenile diseases, Therapeutics |
| Abstract: | Background: ChatGPT could be a useful tool in the infectious disease field. However, the application of ChatGPT for the treatment of infectious diseases in vulnerable population has not been determined. Methods: We designed questions about antibiotic use, including the choice of antibiotics, dose, and treatment duration for prevalent infectious disease in vulnerable populations. Each query was posed to ChatGPT-4, and the answers were independently evaluated by two authors. When there were significant differences in the final scores between the two authors, they discussed the case and answers to obtain results. Results: Our analysis revealed that 38.1% of responses were comprehensive and correct, with 11.9% containing errors for medication use for patients during pregnancy. For the antibiotic allergy-related questions, 36.1% of responses were comprehensive and correct, and 18.1% contained errors. For older adults, 27.5% of responses were comprehensive and correct, while 25% contained errors. The error rate in patients with kidney disease was 79.2%. For children, 43.8% of answers contained errors. Conclusion: ChatGPT produced high rates of inaccurate information for treating infectious diseases in special population. Thus, recommendations generated by ChatGPT should be used with caution and checked by healthcare professionals to ensure accuracy and comprehensiveness prior to use. [ABSTRACT FROM AUTHOR] |
| Copyright of Annals of Biomedical Engineering is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
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