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相关概念视频

Classification of Illness01:17

Classification of Illness

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The meaning of illness is individualized to each person who experiences an alteration in health. In contrast, disease is a medical term indicating a pathological change in the structure and function of the body or mind. It is a condition that has specific symptoms and boundaries.
An illness is a response to a disease in which the person's level of functioning is changed compared with a previous level. The general classification of illness includes acute and chronic.
Acute illness is severe...
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Methods of Documentation VI: Case Management Model01:15

Methods of Documentation VI: Case Management Model

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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.
For example, a patient with a chronic...
633
Formulating and Validating Nursing Diagnosis I01:26

Formulating and Validating Nursing Diagnosis I

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A nursing diagnosis is written when the nurse recognizes a cluster of essential patient data indicating health problems treated with independent nursing interventions. The standardized terminologies of a nursing diagnosis help nurses identify and treat patients' problems. Every electronic health record that uses nursing diagnosis must employ standard diagnostic terminology. Developing an efficient, individualized care plan begins with accurate nursing diagnoses.
There are thirteen domains...
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Survival Tree01:19

Survival Tree

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Survival trees are a non-parametric method used in survival analysis to model the relationship between a set of covariates and the time until an event of interest occurs, often referred to as the "time-to-event" or "survival time." This method is particularly useful when dealing with censored data, where the event has not occurred for some individuals by the end of the study period, or when the exact time of the event is unknown.
 Building a Survival Tree
Constructing a...
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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.
Critical attributes of NCIS include:
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Nursing Interventions II: Selecting and Classifying the Nursing Interventions01:29

Nursing Interventions II: Selecting and Classifying the Nursing Interventions

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Creating and executing a nursing diagnosis helps nurses plan care and guide patient, family, and community interventions. They are developed based on a patient's physical evaluation and support measuring the outcomes. It is not recommended to select random interventions throughout the planning process. Instead, consider the following six essential factors when choosing interventions:
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A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts
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基于临床文本树结构的ICD代码映射模型.

Jingjin Xue1, Pengli Lu1

  • 1School of Computer and Communication, Lanzhou University of Technology, Lanzhou 730050, China.

Artificial intelligence in medicine
|May 30, 2025
PubMed
概括

通过深度学习,TRIC模型增强了临床记录的自动国际疾病分类 (ICD) 编码. 这种用于ICD编码 (TRIC) 的变压器和树木模型提高了医疗记录分类的准确性和效率.

科学领域:

  • 人工智能的人工智能
  • 医疗信息学 医疗信息学
  • 自然语言处理自然语言处理.

背景情况:

  • 深度学习方法提高了电子医疗记录 (EMR) 编码效率,取代了手工流程.
  • 在表示临床文本语义和结合结构记录特征方面仍然存在挑战.
  • 现有的模型在处理非结构化临床数据的复杂性方面扎,以获得准确的ICD编码.

研究的目的:

  • 为增强的自动ICD编码提出TRansformer和TRee-lstm用于ICD编码 (TRIC) 模型.
  • 解决临床记录中语义表示和结构特征提取方面的局限性.
  • 为了提高非结构化临床文本与ICD代码的映射的准确性和效率.

主要方法:

  • TRIC模型整合了选区树和基于变压器的模型来进行特征提取.
  • 树-lstm用于丰富临床记录特征.
  • 生物BERT用于突出显示关键的ICD编码元素并改善匹配.
  • 一个完全连接的神经网络分类器执行许多对许多映射.

主要成果:

  • 与12个基准模型相比,TRIC模型在MIMIC-III数据集上取得了更好的表现.
  • 关键的绩效指标包括MiF (0.586),MaF (0.109),MiAUC (0.989),MaAUC (0.937) 和P@8 (0.758) 等.
关键词:
选区树是一个选区树.在ICD自动编码.多个标签的文本分类.语义上的相似性 语义上的相似性树的最后一个.

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  • 这些结果显示了自动ICD编码质量的显著改善.

    • 结论:

    • TRIC模型有效地解决了临床记录中语义表示和结构特征的挑战.
    • 它为准确和高效的非结构化EMR数据的自动ICD编码提供了强大的解决方案.
    • 该研究验证了TRIC模型提高ICD自动编码质量的能力.