Assessing the Current Limitations of Large-Language Models in Advancing Healthcare Education (Preprint) DOI Creative Commons

Janghyeon Kim,

Bathri Vajravelu

JMIR Formative Research, Journal Year: 2024, Volume and Issue: 9, P. e51319 - e51319

Published: Sept. 3, 2024

The 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. practical use current LLMs in sparks great anticipation for new avenues, yet its embracement also elicits considerable concerns that necessitate careful deliberation. This study aims to evaluate application state-of-the-art education, highlighting following shortcomings areas requiring significant urgent improvements: (1) threats academic integrity, (2) dissemination misinformation risks automation bias, (3) challenges information completeness consistency, (4) inequity access, (5) algorithmic (6) exhibition moral instability, (7) technological limitations plugin tools, (8) lack regulatory oversight addressing legal ethical challenges. Future research should focus on strategically persistent highlighted this paper, opening door effective measures can improve their education.

Language: Английский

Can deepseek and ChatGPT be used in the diagnosis of oral pathologies? DOI Creative Commons
Ömer Faruk Kaygisiz,

Mehmet Turhan Teke

BMC Oral Health, Journal Year: 2025, Volume and Issue: 25(1)

Published: April 25, 2025

Language: Английский

Citations

0

Assessing the Current Limitations of Large-Language Models in Advancing Healthcare Education (Preprint) DOI Creative Commons

Janghyeon Kim,

Bathri Vajravelu

JMIR Formative Research, Journal Year: 2024, Volume and Issue: 9, P. e51319 - e51319

Published: Sept. 3, 2024

The 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. practical use current LLMs in sparks great anticipation for new avenues, yet its embracement also elicits considerable concerns that necessitate careful deliberation. This study aims to evaluate application state-of-the-art education, highlighting following shortcomings areas requiring significant urgent improvements: (1) threats academic integrity, (2) dissemination misinformation risks automation bias, (3) challenges information completeness consistency, (4) inequity access, (5) algorithmic (6) exhibition moral instability, (7) technological limitations plugin tools, (8) lack regulatory oversight addressing legal ethical challenges. Future research should focus on strategically persistent highlighted this paper, opening door effective measures can improve their education.

Language: Английский

Citations

3