Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Modeling in Therapy01:26

Modeling in Therapy

593
Modeling, a key technique in therapy, uses observational learning to help clients acquire and practice new skills by watching therapists demonstrate desired behaviors. This approach, rooted in Albert Bandura's concept of vicarious learning, plays a significant role in therapeutic interventions for various psychological conditions, including social anxiety, ADHD, and depression.
Participant Modeling
Participant modeling involves therapists demonstrating calm and effective behaviors in...
593
Diagnostic and Statistical Manual of Mental Disorders (DSM)01:27

Diagnostic and Statistical Manual of Mental Disorders (DSM)

1.4K
The Diagnostic and Statistical Manual of Mental Disorders (DSM) serves as the primary classification system for mental health disorders, providing standardized diagnostic criteria for clinicians and researchers. First published by the American Psychiatric Association (APA) in 1952, the DSM has undergone several revisions to reflect evolving psychiatric understanding. The fifth edition, DSM-5, released in 2013, introduced key updates that expanded diagnostic categories and modified diagnostic...
1.4K
Documentation of Nursing Diagnosis01:10

Documentation of Nursing Diagnosis

1.9K
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...
1.9K
Data Validation01:03

Data Validation

7.1K
Data validation is an essential part of a comprehensive assessment. Validation is confirming or verifying and opening the door to gathering more assessment data as it clarifies vague or unclear data. The process of checking and verifying the collected information is called data validation. The primary purpose of data validation is to ensure data is as free from error, bias, and misinterpretation as possible.
Nursing assessment guides are generally based on holistic models rather than medical...
7.1K
Formulating and Validating Nursing Diagnosis I01:26

Formulating and Validating Nursing Diagnosis I

4.2K
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...
4.2K

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

New Paradigm of Identifiable General-response Cognitive Diagnostic Models: Beyond Categorical Data.

Psychometrika·2026
Same author

Spectral Clustering with Likelihood Refinement for High-Dimensional Latent Class Recovery.

Psychometrika·2026
Same author

Constructive <i>Q</i>-Matrix Identifiability via Novel Tensor Unfolding.

Psychometrika·2026
Same author

Exploratory General-Response Cognitive Diagnostic Models with Higher-Order Structures.

Psychometrika·2025
Same author

New Paradigm of Identifiable General-response Cognitive Diagnostic Models: Beyond Categorical Data.

Psychometrika·2024
Same author

A Spectral Method for Identifiable Grade of Membership Analysis with Binary Responses.

Psychometrika·2024

相关实验视频

Updated: Feb 26, 2026

Event Related Potentials ERPs and other EEG Based Methods for Extracting Biomarkers of Brain Dysfunction: Examples from Pediatric Attention Deficit/Hyperactivity Disorder ADHD
10:02

Event Related Potentials ERPs and other EEG Based Methods for Extracting Biomarkers of Brain Dysfunction: Examples from Pediatric Attention Deficit/Hyperactivity Disorder ADHD

Published on: March 12, 2020

16.8K

深入研究诊断建模:深度认知诊断模型 (DeepCDMs)

Yuqi Gu1

  • 1Columbia University.

Psychometrika
|February 25, 2026
PubMed
概括

我们介绍了深度认知诊断模型 (DeepCDMs),这是一种提高教育测量的新方法. 深度CDM提供了更好的识别性,节性和解释性,用于诊断认知技能.

科学领域:

  • 教育测量和心理测量学
  • 机器学习 机器学习
  • 人工智能的人工智能

背景情况:

  • 认知诊断模型 (CDM) 在教育和心理测量中广泛用于离散潜变量建模.
  • 现有的CDM在识别,储蓄和解释方面面临挑战,特别是在复杂的诊断场景中.
  • 深度生成建模为捕获复杂的数据结构和改进模型属性提供了潜在的优势.

研究的目的:

  • 通过将深度生成建模与CDM原则相结合,提出一个新的深度认知诊断模型 (DeepCDMs) 家族.
  • 通过提高认知诊断中的识别性,节性和解释性来解决传统CDM的局限性.
  • 为深度离散诊断建模开发理论上健全和实践上适用的方法.

主要方法:

  • 介绍了DeepCDMs,这是一种利用深度生成架构进行认知诊断的新型模型类.
  • 建立了DeepCDM识别的数学条件,包括所有深度的唯一参数和Q矩阵识别.
  • 开发了贝叶斯式配方和高效的吉布斯采样算法,用于在已知Q矩阵的确认设置中进行参数估计.

主要成果:

  • 证明DeepCDMs完全可以识别,即使在探索性设置中,也可以独特地确定参数和Q矩阵.
  • 展示了DeepCDMs的统计储蓄性,因为模型深度,可以使用更少的参数进行表达式数据建模.
关键词:
贝叶斯的推理 贝叶斯的推理贝叶斯网络是一个贝叶斯网络.深度CDMCDM深度CDMCDM深度CDMCDM这就是Q矩阵.认知诊断模型是一个认知诊断模型.深度生成模型深度生成模型深度学习是一种深度学习.指向图形模型的指向图形模型.可以识别的可识别性

更多相关视频

Assessing Dyslexia at Six Year of Age
15:00

Assessing Dyslexia at Six Year of Age

Published on: May 1, 2020

8.9K
Author Spotlight: Advancing Alzheimer's Research &#8211; Exploring Early Detection and Multi-Omics Approaches
09:47

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches

Published on: December 15, 2023

1.9K

相关实验视频

Last Updated: Feb 26, 2026

Event Related Potentials ERPs and other EEG Based Methods for Extracting Biomarkers of Brain Dysfunction: Examples from Pediatric Attention Deficit/Hyperactivity Disorder ADHD
10:02

Event Related Potentials ERPs and other EEG Based Methods for Extracting Biomarkers of Brain Dysfunction: Examples from Pediatric Attention Deficit/Hyperactivity Disorder ADHD

Published on: March 12, 2020

16.8K
Assessing Dyslexia at Six Year of Age
15:00

Assessing Dyslexia at Six Year of Age

Published on: May 1, 2020

8.9K
Author Spotlight: Advancing Alzheimer's Research &#8211; Exploring Early Detection and Multi-Omics Approaches
09:47

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches

Published on: December 15, 2023

1.9K
  • 突出了DeepCDMs的实际可解释性,其深度架构可促进从粗到细的多颗粒度技能诊断.
  • 结论:

    • DeepCDMs代表了认知诊断建模的重大进步,提供了增强的识别性,节性和可解释性.
    • 拟议的方法提供了一个强大的框架,用于深度离散的诊断建模,具有透明的识别条件.
    • 从模拟和应用到TIMSS 2019数据的实证证据证实了DeepCDMs的实用性和有效性.