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

Bias01:22

Bias

4.2K
Bias refers to any tendency that prevents a question from being considered unprejudiced. In research, bias occurs when one outcome or answer is selected or encouraged over others in sampling or testing. Bias can occur during any research phase, including study design, data collection, analysis, and publication.
In statistics, a sampling bias is created when a sample is collected from a population, and some members of the population are not as likely to be chosen as others (remember, each member...
4.2K
Introduction to Cognitive Psychology01:20

Introduction to Cognitive Psychology

490
Cognitive psychology is the field of psychology dedicated to examining how people think. It attempts to explain how and why we think the way we do by studying the interactions among human thinking, emotion, creativity, language, and problem-solving, as well as other cognitive processes. Cognitive psychology studies how information is processed and manipulated in remembering, thinking, and knowing.
This field emerged in the mid-20th century, following a period dominated by behaviorism, which...
490
Confirmation Biases01:31

Confirmation Biases

5.5K
The confirmation bias is the tendency to focus on information that confirms our existing beliefs and ignore information that is inconsistent with our expectations. For example, if you think that your professor is not very nice, you notice all of the instances of rude behavior exhibited by the professor while ignoring the countless pleasant interactions he is involved in on a daily basis. Have you ever fallen prey to the confirmation bias, either as the source or target of such bias?
5.5K
Stereotype Content Model02:16

Stereotype Content Model

14.7K
The Stereotype Content Model (SCM) was first proposed by Susan Fiske and her colleagues (Fiske, Cuddy, Glick & Xu, 2002; see also Fiske, 2012 and Fiske, 2017). The SCM specifies that when someone encounters a new group, they will stereotype them based on two metrics: warmth—or that group’s perceived intent, and how likely they are to provide help or inflict harm—and competence—or their ability to carry out that objective. Depending on the warmth-competence...
14.7K
Stereotypes, Prejudice, and Discrimination02:55

Stereotypes, Prejudice, and Discrimination

90.2K
Humans are very diverse and although we share many similarities, we also have many differences. The social groups we belong to help form our identities (Tajfel, 1974). These differences may be difficult for some people to reconcile, which may lead to prejudice toward people who are different. Prejudice is a negative attitude and feeling toward an individual based solely on one’s membership in a particular social group (Allport, 1954; Brown, 2010). Prejudice is common against people who...
90.2K
Bias in Epidemiological Studies01:29

Bias in Epidemiological Studies

280
Biases can arise at various stages of research, from study design and data collection to analysis and interpretation. Recognizing and addressing these biases is essential to ensure the validity and reliability of epidemiological findings.Broadly speaking, biases in epidemiology fall into three main categories: selection bias, information bias, and confounding. A more detailed description of possible biases is:  
280

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

Proton Density MRI for Evaluation of Neurovascular Structures Involved in Trigeminal Neuralgia.

AJNR. American journal of neuroradiology·2026
Same author

Alignment of Policy, Practice, and Patient Safety for Trustworthy AI in Radiology.

Radiology. Artificial intelligence·2026
Same author

Sinking Flap Syndrome: Risk Factors, Outcomes, and the Role of Neuroradiology in Cranioplasty Timing.

AJNR. American journal of neuroradiology·2026
Same author

Connectome disruptions after hypoxic-ischaemic injury associate with consciousness disorder severity.

Brain communications·2026
Same author

Neuroimaging in Low- to Middle-Income Countries: A Health Equity Perspective.

AJNR. American journal of neuroradiology·2026
Same author

Multisystemic Imaging Features of Coccidioidomycosis.

Radiographics : a review publication of the Radiological Society of North America, Inc·2026

相关实验视频

Updated: Jul 7, 2025

Characterization of the Sense of Agency over the Actions of Neural-machine Interface-operated Prostheses
05:21

Characterization of the Sense of Agency over the Actions of Neural-machine Interface-operated Prostheses

Published on: January 7, 2019

7.9K

了解人工智能中的偏见:从实践的角度来看

Melissa A Davis1, Ona Wu2, Ichiro Ikuta3

  • 1From Yale University (M.A.D., M.H.J.), New Haven, Connecticut Melissa.a.davis@yale.edu.

AJNR. American journal of neuroradiology
|December 20, 2023
PubMed
概括
此摘要是机器生成的。

神经放射学中的人工智能 (AI) 需要对健康公平偏见进行仔细评估. 这种观点引导神经放射学家评估人工智能工具,以确保公平的放射性护理.

更多相关视频

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
05:47

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

Published on: June 13, 2025

225
Author Spotlight: Advancing CBCT and Digital Dental Image Integration with AI-Assisted Digitization
05:49

Author Spotlight: Advancing CBCT and Digital Dental Image Integration with AI-Assisted Digitization

Published on: February 23, 2024

866

相关实验视频

Last Updated: Jul 7, 2025

Characterization of the Sense of Agency over the Actions of Neural-machine Interface-operated Prostheses
05:21

Characterization of the Sense of Agency over the Actions of Neural-machine Interface-operated Prostheses

Published on: January 7, 2019

7.9K
Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
05:47

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

Published on: June 13, 2025

225
Author Spotlight: Advancing CBCT and Digital Dental Image Integration with AI-Assisted Digitization
05:49

Author Spotlight: Advancing CBCT and Digital Dental Image Integration with AI-Assisted Digitization

Published on: February 23, 2024

866

科学领域:

  • 神经辐射学神经辐射学
  • 人工智能的人工智能
  • 健康 公平 卫生 公平

背景情况:

  • 美国神经辐射学会 (ASNR) 多样性和包容性委员会主办了一场关于人工智能 (AI) 在医疗保健中的偏见的网络研讨会.
  • 了解和减轻人工智能工具中的偏见对于确保公平的放射性护理至关重要.
  • 神经放射学家必须参与不断发展的AI技术,以保持持续的学习和道德实践.

研究的目的:

  • 从ASNR网络研讨会中提取关于神经放射学中人工智能偏见的关键概念.
  • 为神经放射学家提供一个框架来评估人工智能工具中的健康公平相关偏见.
  • 通过临床工作流程示例,探索AI对公平放射治疗的影响.

主要方法:

  • 来自ASNR网络研讨会的主要讨论点的提炼.
  • 开发一个框架来评估AI工具的健康公平偏见.
  • 介绍了AI在神经放射学中的临床工作流实施示例.

主要成果:

  • 确定了解决神经放射学家对人工智能偏见的重要性.
  • 为开发评估AI偏见的框架提供了见解.
  • 强调了人工智能对公平放射性护理的潜在影响.

结论:

  • 神经放射学家需要积极评估AI工具的潜在偏见.
  • 结构化的框架对于评估人工智能应用中的健康公平至关重要.
  • 与人工智能互动对于推进放射治疗中的公平实践至关重要.