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

Self-Schemas02:16

Self-Schemas

31.1K
In general, a schema is a mental construct consisting of a cluster or collection of related concepts (Bartlett, 1932). There are many different types of schemata, and they all have one thing in common: schemata are a method of organizing information that allows the brain to work more efficiently. When a schema is activated, the brain makes immediate assumptions about the person or object being observed.
31.1K
Schemas01:42

Schemas

11.6K
A schema is a mental construct consisting of a cluster or collection of related concepts (Bartlett, 1932). There are many different types of schemata, and they all have one thing in common: schemata are a method of organizing information that allows the brain to work more efficiently. When a schema is activated, the brain makes immediate assumptions about the person or object being observed.
11.6K
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

53
Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
53
Levels of Use of a GIS01:29

Levels of Use of a GIS

49
Geographic Information Systems (GIS) operate across three levels of application, each representing an increasing degree of complexity: data management, analysis, and prediction. These levels reflect the expanding functionality and versatility of GIS technology in handling spatial data for diverse purposes.Data ManagementAt its foundational level, GIS serves as a tool for data management, enabling the input, storage, retrieval, and organization of spatial data. This level is often employed in...
49
Woodward–Hoffmann Selection Rules and Microscopic Reversibility01:34

Woodward–Hoffmann Selection Rules and Microscopic Reversibility

3.1K
Electrocyclic reactions, cycloadditions, and sigmatropic rearrangements are concerted pericyclic reactions that proceed via a cyclic transition state. These reactions are stereospecific and regioselective. The stereochemistry of the products depends on the symmetry characteristics of the interacting orbitals and the reaction conditions. Accordingly, pericyclic reactions are classified as either symmetry-allowed or symmetry-forbidden. Woodward and Hoffmann presented the selection criteria for...
3.1K
Schemata01:17

Schemata

80
A schema is a mental construct that organizes related concepts, allowing the brain to process information efficiently. Upon activation, schemata facilitate assumptions about people or objects.
Two types of schemata are:
80

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

Eco-anxiety and the collective action problem of climate change alarmism.

Australasian psychiatry : bulletin of Royal Australian and New Zealand College of Psychiatrists·2026
Same author

Operationalising readiness for practice in final OSCEs: insights from a mixed-methods study across five Australian medical schools.

BMC medical education·2026
Same author

Rural Medical Education: Finding the Right Recipe.

The Australian journal of rural health·2026
Same author

'Communication Is Crucial': A Qualitative Study of Patient Expectations of Diagnostic Tests in Emergency Medicine Practice.

Health expectations : an international journal of public participation in health care and health policy·2026
Same author

Assessing the Utility of AI Versus Human-Created MCQs in Pediatric Medical Education.

Journal of medical education and curricular development·2026
Same author

Turning struggles into strengths: A qualitative exploration of academic difficulty in medical school.

Medical teacher·2026

相关实验视频

Updated: Jun 28, 2025

The Spatial Memory Game: Testing the Relationship Between Spatial Language, Object Knowledge, and Spatial Cognition
05:15

The Spatial Memory Game: Testing the Relationship Between Spatial Language, Object Knowledge, and Spatial Cognition

Published on: February 19, 2018

10.8K

验证由自我组织地图所代表的知识,并具有专家衍生知识结构.

Andrew James Amos1, Kyungmi Lee2, Tarun Sen Gupta3

  • 1College of Medicine & Dentistry, James Cook University, Townsville, Australia. Andrew.Amos@jcu.edu.au.

BMC medical education
|April 16, 2024
PubMed
概括
此摘要是机器生成的。

像MedSOM这样的机器学习可视化可以通过连贯地总结教科书参考来验证精神病学知识领域. 这增强了对人工智能驱动的医学教育见解的理解和信任.

关键词:
人工智能的人工智能是人工智能.课程的发展课程的发展.可解释的人工智能机器学习是机器学习.医学教育 医学教育科学测量公司的科学测量.

更多相关视频

Modeling the Functional Network for Spatial Navigation in the Human Brain
05:55

Modeling the Functional Network for Spatial Navigation in the Human Brain

Published on: October 13, 2023

1.1K
Temporal Ordering of Dynamic Expression Data from Detailed Spatial Expression Maps
11:52

Temporal Ordering of Dynamic Expression Data from Detailed Spatial Expression Maps

Published on: February 9, 2017

5.9K

相关实验视频

Last Updated: Jun 28, 2025

The Spatial Memory Game: Testing the Relationship Between Spatial Language, Object Knowledge, and Spatial Cognition
05:15

The Spatial Memory Game: Testing the Relationship Between Spatial Language, Object Knowledge, and Spatial Cognition

Published on: February 19, 2018

10.8K
Modeling the Functional Network for Spatial Navigation in the Human Brain
05:55

Modeling the Functional Network for Spatial Navigation in the Human Brain

Published on: October 13, 2023

1.1K
Temporal Ordering of Dynamic Expression Data from Detailed Spatial Expression Maps
11:52

Temporal Ordering of Dynamic Expression Data from Detailed Spatial Expression Maps

Published on: February 9, 2017

5.9K

科学领域:

  • 医疗信息学 医疗信息学
  • 人工智能在医学中的应用
  • 知识表示 知识表示

背景情况:

  • 在医疗保健中采用机器学习 (ML) 的障碍是缺乏可解释性.
  • 医学文献的可视化可以提炼大量的信息,但往往缺乏清晰的含义.
  • 验证ML衍生的见解对于它们在医学课程开发等领域的接受至关重要.

研究的目的:

  • 为了验证自我组织地图 (MedSOM) 可视化的解释性.
  • 评估MedSOM能够连贯地总结精神病学知识的能力.
  • 将ML输出与精神病学中已建立的知识标准联系起来.

主要方法:

  • 在Medline/PubMed索引文章上训练了一个自我组织的地图 (MedSOM).
  • 分析了核心精神病学教科书的十个版本的参考清单.
  • 应用K-means集群对在MedSOM上投射的教科书参考进行了分析.

主要成果:

  • 在10个教科书版本 (1967-2017年) 中,MedSOM始终确定了六个不同的精神病学知识领域.
  • 聚类揭示了在广泛的精神病学实践领域的层面上连贯的组织.
  • 确定的领域包括一般/成人精神病学,儿童精神病学和行政精神病学.

结论:

  • 这项研究证实了MedSOM能够代表和稳定精神病学知识领域的能力.
  • 这表明了验证医学文献的ML驱动可视化方法.
  • 成功验证增强了信任,并促进了在医学教育和课程开发中使用ML见解.