Assessing the Current Limitations of Large Language Models in Advancing Health Care Education
AbstractThe integration of large language models (LLMs), as seen with the generative pretrained transformers series, into health care education and clinical management represents a transformative potential. The practical use of current LLMs in health care sparks great anticipation for new...
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JMIR Publications
2025-01-01
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| Series: | JMIR Formative Research |
| Online Access: | https://formative.jmir.org/2025/1/e51319 |
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| author | JaeYong Kim Bathri Narayan Vajravelu |
| author_facet | JaeYong Kim Bathri Narayan Vajravelu |
| author_sort | JaeYong Kim |
| collection | DOAJ |
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AbstractThe integration of large language models (LLMs), as seen with the generative pretrained transformers series, into health care education and clinical management represents a transformative potential. The practical use of current LLMs in health care sparks great anticipation for new avenues, yet its embracement also elicits considerable concerns that necessitate careful deliberation. This study aims to evaluate the application of state-of-the-art LLMs in health care education, highlighting the following shortcomings as areas requiring significant and urgent improvements: (1) threats to academic integrity, (2) dissemination of misinformation and risks of automation bias, (3) challenges with information completeness and consistency, (4) inequity of access, (5) risks of algorithmic bias, (6) exhibition of moral instability, (7) technological limitations in plugin tools, and (8) lack of regulatory oversight in addressing legal and ethical challenges. Future research should focus on strategically addressing the persistent challenges of LLMs highlighted in this paper, opening the door for effective measures that can improve their application in health care education. |
| format | Article |
| id | doaj-art-d065b19308324e90b5e376fe0709d5c9 |
| institution | Kabale University |
| issn | 2561-326X |
| language | English |
| publishDate | 2025-01-01 |
| publisher | JMIR Publications |
| record_format | Article |
| series | JMIR Formative Research |
| spelling | doaj-art-d065b19308324e90b5e376fe0709d5c92025-01-27T02:58:40ZengJMIR PublicationsJMIR Formative Research2561-326X2025-01-019e51319e5131910.2196/51319Assessing the Current Limitations of Large Language Models in Advancing Health Care EducationJaeYong Kimhttp://orcid.org/0009-0008-5855-7676Bathri Narayan Vajraveluhttp://orcid.org/0000-0002-1558-2651 AbstractThe integration of large language models (LLMs), as seen with the generative pretrained transformers series, into health care education and clinical management represents a transformative potential. The practical use of current LLMs in health care sparks great anticipation for new avenues, yet its embracement also elicits considerable concerns that necessitate careful deliberation. This study aims to evaluate the application of state-of-the-art LLMs in health care education, highlighting the following shortcomings as areas requiring significant and urgent improvements: (1) threats to academic integrity, (2) dissemination of misinformation and risks of automation bias, (3) challenges with information completeness and consistency, (4) inequity of access, (5) risks of algorithmic bias, (6) exhibition of moral instability, (7) technological limitations in plugin tools, and (8) lack of regulatory oversight in addressing legal and ethical challenges. Future research should focus on strategically addressing the persistent challenges of LLMs highlighted in this paper, opening the door for effective measures that can improve their application in health care education.https://formative.jmir.org/2025/1/e51319 |
| spellingShingle | JaeYong Kim Bathri Narayan Vajravelu Assessing the Current Limitations of Large Language Models in Advancing Health Care Education JMIR Formative Research |
| title | Assessing the Current Limitations of Large Language Models in Advancing Health Care Education |
| title_full | Assessing the Current Limitations of Large Language Models in Advancing Health Care Education |
| title_fullStr | Assessing the Current Limitations of Large Language Models in Advancing Health Care Education |
| title_full_unstemmed | Assessing the Current Limitations of Large Language Models in Advancing Health Care Education |
| title_short | Assessing the Current Limitations of Large Language Models in Advancing Health Care Education |
| title_sort | assessing the current limitations of large language models in advancing health care education |
| url | https://formative.jmir.org/2025/1/e51319 |
| work_keys_str_mv | AT jaeyongkim assessingthecurrentlimitationsoflargelanguagemodelsinadvancinghealthcareeducation AT bathrinarayanvajravelu assessingthecurrentlimitationsoflargelanguagemodelsinadvancinghealthcareeducation |