导航生物医学研究中的学术完整性:大型语言模型对当前实践和未来方向的影响
Anqi Lin1, Zuwei Chen1, Aimin Jiang2
1Donghai County People's Hospital (Affiliated Kangda College of Nanjing Medical University); Department of Oncology, Zhujiang Hospital, Southern Medical University, Lianyungang, China.
International journal of surgery (London, England)
|December 11, 2025
概括
大型语言模型 (LLM) 提供了诸如提高研究效率等好处,但也对生物医学学术完整性构成风险. 解决方案侧重于政策,人工智能素养和改进的同行评审,以确保负责任的使用.
科学领域:
- 生物医学研究的研究.
- 人工智能的人工智能是人工智能.
- 学术诚信 学术诚信
背景情况:
- 大型语言模型 (LLM) 越来越多地在各个学科中使用,但它们对学术完整性的影响,特别是生物医学方面,研究不足.
- 学术诚信在生物医学领域至关重要,需要对LLM影响进行检查.
研究的目的:
- 分析LLM对生物医学领域的学术诚信所带来的机遇和挑战.
- 提出优化LLMs有益应用的策略,同时降低风险.
主要方法:
- 对LLM能力及其对学术实践的影响进行系统审查和分析.
- 开发一个多维框架来解决与LLM相关的完整性问题.
主要成果:
- 法律法规可以提高研究效率和质量,但也有可能促进不当行为,不准确性,偏见和错误信息.
- 潜在的挑战包括妥协的同行评审和破坏高等教育.
结论:
- 士课程为生物医学学术诚信带来了重大机遇和挑战.
- 包括政策,人工智能素养,技术工具和道德准则在内的综合方法对于维护完整性至关重要.
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