医学中的生成人工智能:对应用,挑战和未来前景的彻底检查
S Jayasrilakshmi1, Ansuman Mahapatra1
1Department of Computer Science and Engineering, NIT Puducherry, Karaikal, India.
Computers in biology and medicine
|January 20, 2026
概括
生成型人工智能,特别是大型语言模型 (LLM),正在通过改进诊断,患者管理和研究来彻底改变医疗保健. 这篇评论探讨了医学领域的LLM应用,强调了好处和挑战.
科学领域:
- 人工智能在医学中的应用
- 在医疗保健中的自然语言处理.
- 数字化健康转型
背景情况:
- 生成型人工智能,包括ChatGPT和Bard等先进模型,正在越来越多地影响医疗保健部门.
- 大型语言模型 (LLM) 为疾病预测,风险因素识别和提高诊断准确性提供了重大潜力.
- 对庞大且分布不均的医疗数据的分析是LLM可以提供实质价值的关键领域.
研究的目的:
- 提供关于LLM在医疗保健中的应用现有文献的全面审查.
- 为包括普通读者,医疗保健专业人员和研究人员在内的各种受众阐明语言模型的当前状态 ("现状").
- 调查医疗保健领域内LLM的多方面的能力.
主要方法:
- 关于医疗保健中大型语言模型的当前研究的文献综述.
- 基于人体器官系统的LLM应用程序的分类,用于有针对性的信息检索.
- 分析LLM在咨询,患者管理,教育,资源利用和临床研究等领域的能力.
主要成果:
- 在医疗咨询,患者管理和治疗策略方面,LLM展示了变革性的潜力.
- 在医学教育,资源优化和通过LLM整合加速临床研究方面取得了重大进展.
- 文献综述强调了广泛的LLM应用程序,由医学专业组织,提供了该领域的结构化概述.
结论:
- 法律学代表着一个重要的技术进步,有可能重塑医疗保健行业的各个方面.
- 了解LLM的好处,挑战和局限性对于其在医疗保健中的有效和道德实施至关重要.
- 本综述为医疗专业人员,研究人员和行业利益相关者提供了有价值的见解,以导航医学中AI不断变化的格局.
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