通过大型语言模型推进眼科:应用,挑战和未来方向
Qi Zhang1, Shaopan Wang2, Xu Wang1
1School of Computer, University of South China, Hengyang, 421001, China.
Survey of ophthalmology
|March 3, 2025
概括
大型语言模型 (LLM) 通过帮助诊断和研究来改变眼科医学的前景,但面临着数据隐私和AI幻觉等挑战. 这些人工智能工具的安全临床整合需要进一步开发.
科学领域:
- 眼科医生 眼科 眼科
- 人工智能的人工智能
- 医疗信息学 医疗信息学
背景情况:
- 人工智能 (AI) 和大型语言模型 (LLM) 正在迅速发展.
- 法律法学有潜力彻底改变医疗实践,提高护理效率和质量.
- 眼科是LLM可以提供显著好处的一个关键领域.
研究的目的:
- 总结目前LLMs在眼科中的应用.
- 突出在临床眼科中使用LLM的挑战和局限性.
- 为未来将LLM纳入眼科实践提供见解.
主要方法:
- 对眼科LLM应用近期进展的文献综述.
- 分析LLM在诊断,治疗,病历和研究方面的能力.
- 识别和讨论包括知识边界,AI幻觉和数据隐私在内的关键挑战.
主要成果:
- 在眼科疾病诊断和治疗建议方面,LLM有助于.
- LLM提高了医疗记录编写的效率,并提供了教育支持.
- 在数据处理和创新研究方面,LLM支持眼科研究人员.
- 诸如知识限制,人工智能幻觉和数据隐私问题等挑战是普遍存在的.
结论:
- 在眼科中,LLM为临床医生和研究人员提供了大量的支持.
- 解决人工智能幻觉和数据隐私等挑战对于临床采用至关重要.
- 为了在眼科中安全有效地使用LLM,需要进一步的研究和开发.
相关概念视频
02:07Improving Translational Accuracy
Base complementarity between the three base pairs of mRNA codon and the tRNA anticodon is not a failsafe mechanism. Inaccuracies can range from a single mismatch to no correct base pairing at all. The free energy difference between the correct and nearly correct base pairs can be as small as 3 kcal/ mol. With complementarity being the only proofreading step, the estimated error frequency would be one wrong amino acid in every 100 amino acids incorporated. However, error frequencies observed in...
02:07Improving Translational Accuracy
Base complementarity between the three base pairs of mRNA codon and the tRNA anticodon is not a failsafe mechanism. Inaccuracies can range from a single mismatch to no correct base pairing at all. The free energy difference between the correct and nearly correct base pairs can be as small as 3 kcal/ mol. With complementarity being the only proofreading step, the estimated error frequency would be one wrong amino acid in every 100 amino acids incorporated. However, error frequencies observed in...