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相关概念视频

Formulating and Validating Nursing Diagnosis I01:26

Formulating and Validating Nursing Diagnosis I

2.7K
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...
2.7K
Formulating and Validating Nursing Diagnosis II01:25

Formulating and Validating Nursing Diagnosis II

2.8K
Nursing diagnoses represent a problem validated by major defining characteristics. There are four categories of nursing diagnoses: problem-focused, risk, health promotion or wellness, and syndrome. The anatomy of a nursing diagnosis includes three components: problem statement or diagnostic label, defining characteristics, and related factors.
Risk nursing diagnoses represent clinical judgments of an individual, family, or community more vulnerable to developing the health problem than others...
2.8K
Documentation of Nursing Diagnosis01:10

Documentation of Nursing Diagnosis

1.3K
The nurse documents nursing diagnoses and enters them into the patient record. The identified patient's nursing diagnosis is either written out with a plan of care or entered into the electronic health record.
In some settings, data-driven computerized decision support systems are in place, allowing for more accurate nursing diagnoses. The database within one of these systems includes diagnostic labels defining characteristics, activities, and indicators for nursing. A nurse enters...
1.3K
Nursing Diagnosis01:22

Nursing Diagnosis

2.7K
Following assessment, a nursing diagnosis is the next step in the nursing process. It begins after the nurse has collected and recorded the patient data. The purpose of diagnosing is to identify how the client responds to actual or potential health processes, identify factors that bestow or that cause health problems, the etiologies, and identify resources or strengths the individual, group, or community can draw on to prevent or resolve problems.
The nursing diagnosis focuses on evidence-based...
2.7K
Classification of Illness01:17

Classification of Illness

7.5K
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...
7.5K
Intellectual Disability01:29

Intellectual Disability

56
Intellectual disability (ID) is a neurodevelopmental condition characterized by deficits in intellectual and adaptive functioning that manifest during the developmental period. This condition encompasses challenges in reasoning, memory, problem-solving, and learning, accompanied by impairments in everyday life skills, such as communication, self-care, and social interactions. Intellectual disability affects approximately 1% of the population in the United States, impacting an estimated 5...
56

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相关实验视频

Updated: Jul 9, 2025

A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports
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A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports

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基于第一阶逻辑的诊断知识受约束网络,用于综合征差异化.

Meiwen Li1, Lin Wang1, Qingtao Wu1

  • 1School of Information Engineering, Henan University of Science and Technology, Luoyang, 471023, China.

Artificial intelligence in medicine
|December 3, 2023
PubMed
概括

这项研究引入了用于传统中医 (TCM) 综合征差异化的新型深度网络模型,达到89%的准确性. 该模型将TCM知识整合到深度学习中,超越现有方法,并为研究提供新的数据集.

关键词:
深度学习是一种深度学习.第一阶段逻辑是第一阶段逻辑.综合症分化症候群的差异化传统的中国医学是传统的中国医学.

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相关实验视频

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科学领域:

  • 综合医学是一个整体的医学.
  • 医疗保健中的人工智能
  • 计算语言学 计算语言学

背景情况:

  • 传统中医 (TCM) 依赖于综合征分化,这个过程严重依赖于医生的经验.
  • 机器学习的进步为提高TCM综合征差异化的客观性和一致性提供了潜在的解决方案.
  • 现有的深度学习和传统机器学习模型在捕捉TCM诊断原则的细微差别方面存在局限性.

研究的目的:

  • 开发和评估一种用于传统中医综合征差异化的新型深度网络模型.
  • 通过整合领域知识来提高TCM综合征差异化的准确性和可靠性.
  • 为TCM综合征差异化研究引入一个全面的数据集.

主要方法:

  • 提出了一个深度网络模型,通过第一阶段逻辑结合传统中医综合征差异化知识.
  • 开发并利用传统中医综合征差异化 (TSD) 数据集,包含超过4万份临床记录.
  • 将拟议模型的性能与多层感知器 (MLP) 和其他传统机器学习模型进行了比较.

主要成果:

  • 拟议的深度网络模型在TCM综合征分化方面实现了89%的准确性.
  • 该模型显著超过了传统的机器学习模型和MLP深度学习模型.
  • TSD数据集提供疾病,综合征和模式的详细标记,促进进一步的研究.

结论:

  • 新的深度网络模型有效地提高了TCM综合征差异化准确性.
  • 将TCM知识集成到深度学习模型中是客观诊断的一个有希望的方法.
  • TSD数据集是推动TCM综合征差异化研究和探索复杂的医学关系的重要资源.