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相关概念视频

Nursing Clinical Information System01:27

Nursing Clinical Information System

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Nursing Clinical Information System (NCIS)
A Nursing Clinical Information System (NCIS) is a specialized type of healthcare information system tailored to meet the unique needs of nursing practice. It incorporates the principles of nursing informatics to streamline information management and improve the quality of care delivery.
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The discharge summary is crucial as it enables a smooth transition from a healthcare facility to a patient's home or another care setting. This critical document facilitates seamless continuity of care, ensuring patients receive the necessary support and attention.
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Clinical development focuses on how the drug will interact with the human body and encompasses four key phases of clinical trials, each serving a specific purpose in assessing the safety and effectiveness of new drugs. These phases overlap and build upon one another. Phase I involves a small group of healthy volunteers (typically 20-80 individuals) or, in cases where significant toxicity is expected, patients with the targeted disease, such as cancer or AIDS. The volunteers are tested for...
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Focusing involves centering a conversation on a message's critical elements or concepts. Focusing is valuable if the talk is vague or patients begin to repeat themselves. Sometimes, when patients are asked about their symptoms, they may go off-topic and try to tell their entire life story. Respectfully, the nurse should bring the conversation back into focus.
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相关实验视频

Updated: Jun 14, 2025

A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts
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加强了ICD-10对临床文本的代码分配:基于总结的方法.

Yaoqian Sun1, Lei Sang2, Dan Wu1

  • 1College of Biomedical Engineering and Instrument Science, Zhejiang University, Zheda Road, 310027 Hangzhou, Zhejiang Province, China.

Artificial intelligence in medicine
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概括

这项研究引入了一种基于总结的新方法,用于国际疾病分类 (ICD) 编码,提高了对临床文本分配ICD-10代码的准确性. 该方法有效地提炼关键信息,优于传统的分类技术.

关键词:
自动化的ICD-10代码分配.自然语言处理自然语言处理.文本匹配对应的结果文本总结 文本总结 文本总结

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科学领域:

  • 医疗信息学 医疗信息学
  • 自然语言处理自然语言处理.
  • 健康 数据科学 数据科学

背景情况:

  • 赋予国际疾病分类 (ICD) 代码对于患者分类,医院管理和统计分析至关重要.
  • 当前的自动化ICD编码方法经常在漫长的临床文本中与高维空间和冗余信息作斗争.
  • 现有的多标签分类方法面临着长文件和庞大的编码空间的挑战.

研究的目的:

  • 开发一种高效准确的自动化方法,用于将国际疾病分类第十次修订 (ICD-10) 代码分配给临床文本.
  • 解决现有的多标签分类方法在处理长长的临床文本和大标签空间方面的局限性.
  • 在ICD编码过程中引入文本总结技术,以改善信息提炼.

主要方法:

  • 一种基于总结的新方法 (SuM),使用知识导向指针网络来提炼和总结临床文本信息.
  • 为高效的ICD-10代码分配提供一个端到端的战略.
  • 一个匹配模型,具有匹配聚合架构,以将摘要与ICD代码对齐,从一个对所有转向一个对一个匹配.

主要成果:

  • SuM方法在12788个ICD-10编码的排放摘要数据集上取得了卓越的性能.
  • 在TOP-50数据集上获得了0.9548的微AUC和0.7977的MRR@10.
  • 在FULL数据集上展示了一致的结果,表明了知识编码器和端到端战略的有效性.

结论:

  • 提出的自动ICD-10代码分配方法有效地捕获来自长期临床文本的关键信息.
  • 与匹配模型集成的文本总结显著提高了临床文本ICD-10编码的性能.
  • SuM方法为提高自动ICD编码的准确性和效率提供了一个有希望的解决方案.