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Pharmacokinetic models are mathematical constructs that represent and predict the time course of drug concentrations in the body, providing meaningful pharmacokinetic parameters. These models are categorized into compartment, physiological, and distributed parameter models.
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Updated: Sep 10, 2025

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
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医生使用大型语言模型:基于大规模查询级数据的定量研究

Lin Qiu1, Chuang Tang2, Xuan Bi3

  • 1Department of Information Systems and Management Engineering, Southern University of Science and Technology, CoE North 907, 1088 Xueyuan Ave, Shenzhen, 518055, China, 86 0755 88012425.

Journal of medical Internet research
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概括
此摘要是机器生成的。

医生主要使用生成人工智能 (GenAI) 进行医学研究,使用情况因性别,年龄和设备而异. 尽管在查询中有一些敏感信息,但患者隐私风险似乎很低.

关键词:
人工智能生成性人工智能创造性人工智能使用生成型的人工智能医疗服务大型语言模型隐私问题

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科学领域:

  • 医疗保健技术
  • 医疗信息学
  • 医学中的人工智能

背景情况:

  • 生成型人工智能 (GenAI) 越来越多地被采用在医疗保健中,但其在现实世界中的医生使用仍未得到充分研究.
  • 现有的研究集中在理论应用上,缺乏对医生实际使用GenAI工具的洞察力.

研究的目的:

  • 量化分析医生在临床和研究工作流程中使用GenAI的模式.
  • 研究GenAI采用的时间趋势和人口变化.
  • 评估与医生GenAI相互作用相关的潜在患者隐私风险.

主要方法:

  • 在8个月内从989名医生收集并分析了106,942个查询和答案对.
  • 使用主题分类来识别普遍的使用情况及其演变.
  • 开发了敏感性分类器,以检测查询中的个人身份信息,以评估隐私风险.

主要成果:

  • 医生主要使用GenAI进行医学研究 (60.2%),而不是临床实践 (12.25%).
  • 与医疗相关的查询随着时间的推移而增加,特别是在最初的使用序列中.
  • 观察到显著的人口差异:女性和年轻的医生更多地使用GenAI进行临床/行政任务,而计算机访问与研究重点相关.

结论:

  • 医生正在整合GenAI,主要是用于研究,也用于临床支持,在人口统计学中具有多样化的使用.
  • 虽然查询中出现了敏感信息,但隐私泄露的整体风险似乎很小.
  • 采用GenAI的模式突显了考虑到医生人口结构和工作流程整合的定制策略的需要.