文献检索文档翻译深度研究
Suppr Zotero 插件Zotero 插件
邀请有礼套餐&价格历史记录

新学期,新优惠

限时优惠:9月1日-9月22日

30天高级会员仅需29元

1天体验卡首发特惠仅需5.99元

了解详情
不再提醒
插件&应用
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
高级版
套餐订阅购买积分包
AI 工具
文献检索文档翻译深度研究
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2025

探索生成式人工智能在骨科教育与培训中的前景、障碍及未来之路。

Exploring prospects, hurdles, and road ahead for generative artificial intelligence in orthopedic education and training.

作者信息

Gupta Nikhil, Khatri Kavin, Malik Yogender, Lakhani Amit, Kanwal Abhinav, Aggarwal Sameer, Dahuja Anshul

机构信息

Department of Pharmacology, All India Institute of Medical Sciences, Bathinda, Punjab, 151001, India.

Department of Orthopedics, Postgraduate Institute of Medical Education and Research (PGIMER) Satellite Centre, Sangrur, Punjab, 148001, India.

出版信息

BMC Med Educ. 2024 Dec 28;24(1):1544. doi: 10.1186/s12909-024-06592-8.


DOI:10.1186/s12909-024-06592-8
PMID:39732679
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11681633/
Abstract

Generative Artificial Intelligence (AI), characterized by its ability to generate diverse forms of content including text, images, video and audio, has revolutionized many fields, including medical education. Generative AI leverages machine learning to create diverse content, enabling personalized learning, enhancing resource accessibility, and facilitating interactive case studies. This narrative review explores the integration of generative artificial intelligence (AI) into orthopedic education and training, highlighting its potential, current challenges, and future trajectory. A review of recent literature was conducted to evaluate the current applications, identify potential benefits, and outline limitations of integrating generative AI in orthopedic education. Key findings indicate that generative AI holds substantial promise in enhancing orthopedic training through its various applications such as providing real-time explanations, adaptive learning materials tailored to individual student's specific needs, and immersive virtual simulations. However, despite its potential, the integration of generative AI into orthopedic education faces significant issues such as accuracy, bias, inconsistent outputs, ethical and regulatory concerns and the critical need for human oversight. Although generative AI models such as ChatGPT and others have shown impressive capabilities, their current performance on orthopedic exams remains suboptimal, highlighting the need for further development to match the complexity of clinical reasoning and knowledge application. Future research should focus on addressing these challenges through ongoing research, optimizing generative AI models for medical content, exploring best practices for ethical AI usage, curriculum integration and evaluating the long-term impact of these technologies on learning outcomes. By expanding AI's knowledge base, refining its ability to interpret clinical images, and ensuring reliable, unbiased outputs, generative AI holds the potential to revolutionize orthopedic education. This work aims to provides a framework for incorporating generative AI into orthopedic curricula to create a more effective, engaging, and adaptive learning environment for future orthopedic practitioners.

摘要

生成式人工智能(AI)以其生成包括文本、图像、视频和音频在内的各种形式内容的能力为特征,已经彻底改变了包括医学教育在内的许多领域。生成式人工智能利用机器学习来创建多样化的内容,实现个性化学习,提高资源可及性,并促进交互式案例研究。这篇叙述性综述探讨了生成式人工智能(AI)在骨科教育和培训中的整合,强调了其潜力、当前挑战和未来发展轨迹。对近期文献进行了综述,以评估当前的应用情况,确定潜在的益处,并概述在骨科教育中整合生成式人工智能的局限性。主要研究结果表明,生成式人工智能通过其各种应用,如提供实时解释、根据学生个体特定需求量身定制的适应性学习材料以及沉浸式虚拟模拟,在加强骨科培训方面具有巨大潜力。然而,尽管具有潜力,但将生成式人工智能整合到骨科教育中仍面临重大问题,如准确性、偏差、输出不一致、伦理和监管问题以及对人工监督的迫切需求。尽管ChatGPT等生成式人工智能模型已经展示出令人印象深刻的能力,但它们目前在骨科考试中的表现仍不理想,这凸显了进一步发展以匹配临床推理和知识应用复杂性的必要性。未来的研究应专注于通过持续研究来应对这些挑战,优化用于医学内容的生成式人工智能模型,探索符合伦理的人工智能使用最佳实践、课程整合,并评估这些技术对学习成果的长期影响。通过扩展人工智能的知识库,提高其解释临床图像的能力,并确保可靠、无偏差的输出,生成式人工智能有望彻底改变骨科教育。这项工作旨在提供一个将生成式人工智能纳入骨科课程的框架,为未来的骨科从业者创造一个更有效、更具吸引力和适应性更强的学习环境。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c7eb/11681633/c1d12ab8cb4e/12909_2024_6592_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c7eb/11681633/3181ecacd20d/12909_2024_6592_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c7eb/11681633/a87ff2da56ed/12909_2024_6592_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c7eb/11681633/c1d12ab8cb4e/12909_2024_6592_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c7eb/11681633/3181ecacd20d/12909_2024_6592_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c7eb/11681633/a87ff2da56ed/12909_2024_6592_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c7eb/11681633/c1d12ab8cb4e/12909_2024_6592_Fig3_HTML.jpg

相似文献

[1]
Exploring prospects, hurdles, and road ahead for generative artificial intelligence in orthopedic education and training.

BMC Med Educ. 2024-12-28

[2]
How to incorporate generative artificial intelligence in nephrology fellowship education.

J Nephrol. 2024-12

[3]
Harnessing the Power of Generative Artificial Intelligence in Pathology Education: Opportunities, Challenges, and Future Directions.

Arch Pathol Lab Med. 2025-2-1

[4]
Artificial intelligence (AI) in restorative dentistry: current trends and future prospects.

BMC Oral Health. 2025-4-18

[5]
Navigating the integration of artificial intelligence in the medical education curriculum: a mixed-methods study exploring the perspectives of medical students and faculty in Pakistan.

BMC Med Educ. 2025-2-20

[6]
Artificial Intelligence in Medical Education: Transforming Learning and Practice.

Cureus. 2025-3-19

[7]
Generative AI in Critical Care Nephrology: Applications and Future Prospects.

Blood Purif. 2024

[8]
A Current Review of Generative AI in Medicine: Core Concepts, Applications, and Current Limitations.

Curr Rev Musculoskelet Med. 2025-4-30

[9]
A review of ophthalmology education in the era of generative artificial intelligence.

Asia Pac J Ophthalmol (Phila). 2024

[10]
Generative artificial intelligence (AI) literacy in nursing education: A crucial call to action.

Nurse Educ Today. 2025-3

引用本文的文献

[1]
Critical thinking in the age of generative AI: implications for health sciences education.

Front Artif Intell. 2025-5-21

[2]
Editorial: Innovations in teaching and learning for Health Professions Educators.

Front Med (Lausanne). 2025-5-20

[3]
Artificial Intelligence in the Diagnosis and Prognostication of the Musculoskeletal Patient.

HSS J. 2025-5-28

[4]
Assessing ChatGPT's Capability as a New Age Standardized Patient: Qualitative Study.

JMIR Med Educ. 2025-5-20

本文引用的文献

[1]
A novel augmented reality-based simulator for enhancing orthopedic surgical training.

Comput Biol Med. 2025-2

[2]
Generative artificial intelligence for small molecule drug design.

Curr Opin Biotechnol. 2024-10

[3]
Evaluation of ChatGPT-Generated Differential Diagnosis for Common Diseases With Atypical Presentation: Descriptive Research.

JMIR Med Educ. 2024-6-21

[4]
Crafting medical MCQs with generative AI: A how-to guide on leveraging ChatGPT.

GMS J Med Educ. 2024

[5]
Effectiveness of AI-powered Chatbots in responding to orthopaedic postgraduate exam questions-an observational study.

Int Orthop. 2024-8

[6]
Leveraging generative AI for clinical evidence synthesis needs to ensure trustworthiness.

J Biomed Inform. 2024-5

[7]
The generative artificial intelligence revolution: How hospitalists can lead the transformation of medical education.

J Hosp Med. 2024-12

[8]
Using generative AI to investigate medical imagery models and datasets.

EBioMedicine. 2024-4

[9]
Development and validation of an objective virtual reality tool for assessing technical aptitude among potential candidates for surgical training.

BMC Med Educ. 2024-3-14

[10]
Performance of Two Artificial Intelligence Generative Language Models on the Orthopaedic In-Training Examination.

Orthopedics. 2024

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

推荐工具

医学文档翻译智能文献检索