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The case management model is a multidisciplinary approach that involves healthcare professionals from diverse disciplines, such as physicians, nurses, therapists, social workers, and pharmacists, working collaboratively to address the various needs of patients. Each healthcare professional brings unique expertise and perspectives, contributing to a more comprehensive understanding of the patient's condition and tailoring treatment plans accordingly.
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Children master language quickly and with relative ease, supported by both biological predisposition and reinforcement. B. F. Skinner (1957) proposed that language is learned through reinforcement, while Noam Chomsky (1965) argued that language acquisition mechanisms are biologically determined.
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Language serves as a bridge between ideas and communication, influencing how individuals perceive and interact with the world. Psychologists have long debated whether language shapes thought or vice versa. This discussion gained grip with Edward Sapir and Benjamin Lee Whorf in the 1940s, who proposed that language determines thought, a concept known as linguistic determinism. They suggested that the vocabulary and structure of a language influence how its speakers think and perceive reality.
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使用大型语言模型开发和评估临床笔记总结系统

Juliana Damasio Oliveira1, Henrique D P Santos2, Ana Helena D P S Ulbrich2

  • 1Institute of A.I. in Healthcare, Porto Alegre, RS, Brazil. juliana@noharm.ai.

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大型语言模型在解释诊断方面表现出接近人类水平的准确性,显示出临床应用的巨大潜力. 这项技术可以帮助医疗专业人员高效地生成患者出院简报等任务.

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科学领域:

  • 医疗保健中的人工智能
  • 自然语言处理
  • 临床信息学

背景情况:

  • 临床笔记包含患者住院的重要数据,但由于体积和复杂性而难以评估.
  • 准确的临床记录总结对于有效的临床决策至关重要.
  • 大型语言模型 (LLM) 提供了一个有前途的方法来生成连贯且与环境相关的临床文本.

研究的目的:

  • 开发一个使用大型语言模型的排放总结系统.
  • 确保该系统满足终端用户,包括医生和患者的实际需求和经验.
  • 建立一个强大的评估框架来评估LLM的表现.

主要方法:

  • 通过在线调查和采访医生和患者收集用户反.
  • 开发了一个评级系统来评估即时有效性.
  • 将LLM产生的输出与人类评估作为基准进行比较.

主要成果:

  • 这项LLM的诊断解释准确度接近人类水平.
  • 该系统有助于医疗保健专业人员完成常规文档任务.
  • 用户反被纳入,以完善系统的实用性.

结论:

  • 在临床环境中,LLM具有显著的潜力.
  • 这项技术可以简化医疗保健文档流程.
  • 在医疗保健中提供决策支持的新途径.