Jove
Visualize
联系我们

相关概念视频

Expected Value01:15

Expected Value

7.8K
The expected value is known as the "long-term" average or mean. This means that over the long term of experimenting over and over, you would expect this average. The expected average is represented by the symbol μ. It is calculated as follows:
7.8K
Determination of Expected Frequency01:08

Determination of Expected Frequency

2.6K
Suppose one wants to test independence between the two variables of a contingency table. The values in the table constitute the observed frequencies of the dataset. But how does one determine the expected frequency of the dataset? One of the important assumptions is that the two variables are independent, which means the variables do not influence each other. For independent variables, the statistical probability of any event involving both variables is calculated by multiplying the individual...
2.6K
Expected Frequencies in Goodness-of-Fit Tests01:19

Expected Frequencies in Goodness-of-Fit Tests

8.7K
A goodness-of-fit test is conducted to determine whether the observed frequency values are statistically similar to the frequencies expected for the dataset. Suppose the expected frequencies for a dataset are equal such as when predicting the frequency of any number appearing when casting a die. In that case, the expected frequency is the ratio of the total number of observations (n)  to the number of categories (k).
8.7K
Hybridoma Technology01:31

Hybridoma Technology

17.6K
Hybridoma technology is used for the large-scale production of monoclonal antibodies. Monoclonal antibodies bind to only a single antigenic determinant or epitope. Such antibodies are used in research, diagnostics, and disease therapy. The hybridoma technology established in 1975 by Georges Köhler and Cesar Milstein was awarded the Nobel Prize in Medicine in 1984 for revolutionizing research and therapy.
Hybridoma Selection
Commonly used fusion techniques — electroporation,...
17.6K
Health Information Technology and Healthcare Information System01:30

Health Information Technology and Healthcare Information System

3.4K
Health Information Technology (HIT)
Health Information Technology, commonly called HIT, integrates advanced information systems and technology in healthcare settings. Its primary functions include:
3.4K
Schemas01:42

Schemas

12.3K
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.
12.3K

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

Clarifying the relationship between biomedical and health informatics and digital health: expert perspectives.

BMJ health & care informatics·2026
Same author

[Semantics in support of clinical research].

Revue medicale suisse·2026
Same author

A Chronic Pain Self-Management Mobile App (Dolodoc): Cross-Sectional Acceptability Study.

JMIR human factors·2026
Same author

Personalizing Mobile Apps for Health Behavioral Change According to Personality: Cross-Sectional Validation of a Preference Matrix.

JMIR human factors·2026
Same author

Factors Influencing the Use of Mobile Apps and Wearables: Pre- and Post-Surgery Quality of Life Assessment Study.

JMIR formative research·2026
Same author

[AI and clinical reasoning : between promises and the risks of "deskilling"].

Revue medicale suisse·2026
Same journal

Revue medicale suisse·2026
Same journal

Revue medicale suisse·2026
Same journal

Revue medicale suisse·2026
Same journal

Revue medicale suisse·2026
Same journal

Revue medicale suisse·2026
Same journal

Revue medicale suisse·2026
查看所有相关文章
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

相关实验视频

Updated: Jan 31, 2026

Fabrication of Nano-engineered Transparent Conducting Oxides by Pulsed Laser Deposition
10:27

Fabrication of Nano-engineered Transparent Conducting Oxides by Pulsed Laser Deposition

Published on: February 27, 2013

16.0K

[不透明技术和透明度:用户期望什么?]

Mina Bjelogrlic1,2, Laëtitia Gosetto1,2, Hugues Turbe1,2

  • 1Service des sciences de l'information médicale, Hôpitaux universitaires de Genève, 1211 Genève 14.

Revue medicale suisse
|January 29, 2026
PubMed
概括
此摘要是机器生成的。

人工智能 (AI) 在法语瑞士越来越多地使用,特别是在医疗保健领域. 本文探讨了围绕人工智能透明度的价值,挑战和正在进行的辩论,以最大限度地提高收益并减轻风险.

更多相关视频

Testing Animal Anxiety in Rats: Effects of Open Arm Ledges and Closed Arm Wall Transparency in Elevated Plus Maze Test
07:54

Testing Animal Anxiety in Rats: Effects of Open Arm Ledges and Closed Arm Wall Transparency in Elevated Plus Maze Test

Published on: June 29, 2018

14.3K
Brain Morphology of Cannabis Users With or Without Psychosis: A Pilot MRI Study
07:30

Brain Morphology of Cannabis Users With or Without Psychosis: A Pilot MRI Study

Published on: August 18, 2020

7.7K

相关实验视频

Last Updated: Jan 31, 2026

Fabrication of Nano-engineered Transparent Conducting Oxides by Pulsed Laser Deposition
10:27

Fabrication of Nano-engineered Transparent Conducting Oxides by Pulsed Laser Deposition

Published on: February 27, 2013

16.0K
Testing Animal Anxiety in Rats: Effects of Open Arm Ledges and Closed Arm Wall Transparency in Elevated Plus Maze Test
07:54

Testing Animal Anxiety in Rats: Effects of Open Arm Ledges and Closed Arm Wall Transparency in Elevated Plus Maze Test

Published on: June 29, 2018

14.3K
Brain Morphology of Cannabis Users With or Without Psychosis: A Pilot MRI Study
07:30

Brain Morphology of Cannabis Users With or Without Psychosis: A Pilot MRI Study

Published on: August 18, 2020

7.7K

科学领域:

  • 医疗保健技术 医疗保健技术 医疗保健技术
  • 人工智能应用的人工智能应用.
  • 医疗信息学医学信息学

背景情况:

  • 人工智能 (AI) 正在融入法语瑞士的日常生活.
  • 人工智能应用已经在临床使用中,影响了患者的护理.
  • 需要了解有关人工智能的当前知识状态和局限性.

研究的目的:

  • 检查人工智能在医疗保健中的透明度价值和挑战.
  • 探索当前关于人工智能透明度有用性和可行性的辩论.
  • 解决了解人工智能系统及其影响的差距.

主要方法:

  • 关于人工智能在医疗保健中的透明度的文献综述.
  • 对当前关于人工智能道德和监管的辩论和讨论进行分析.
  • 对人工智能对患者护理和临床实践的影响的定性评估.

主要成果:

  • 人工智能透明度带来了重大价值,但也带来了重大挑战.
  • 关于人工智能透明度的辩论是分裂的,突出了对其实用性和实用性的不同观点.
  • 了解人工智能系统仍然是一个关键领域,现有知识缺口.

结论:

  • 人工智能透明度对于最大限度地提高医疗保健的好处和最大限度地降低医疗保健风险至关重要.
  • 需要进一步的研究和公开讨论,以了解人工智能实施的复杂性.
  • 解决人工智能理解的盲点对于负责任的创新至关重要.