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相关概念视频

Decision Making: Traditional Method01:14

Decision Making: Traditional Method

4.0K
The process of hypothesis testing based on the traditional method includes calculating the critical value, testing the value of the test statistic using the sample data, and interpreting these values.
First, a specific claim about the population parameter is decided based on the research question and is stated in a simple form. Further, an opposing statement to this claim is also stated. These statements can act as null and alternative hypotheses, out of which a null hypothesis would be a...
4.0K
Deductive Reasoning01:16

Deductive Reasoning

55.2K
Deductive reasoning, or deduction, is the type of logic used in hypothesis-based science. In deductive reasoning, the pattern of thinking moves in the opposite direction as compared to inductive reasoning, which means that it uses a general principle or law to predict specific results. From those general principles, a scientist can deduce and predict the specific results that would be valid as long as the general principles are valid.
For example, a researcher can deduce specific predictions...
55.2K
Reason and Intuition01:37

Reason and Intuition

6.4K
The human brain processes information for decision-making using one of two routes: an intuitive system and a rational system (Epstein, 1994; popularized by Kahneman, 2011 as System 1 and System 2, respectively). The intuitive system is quick, impulsive, and operates with minimal effort, relying on emotions or habits to provide cues for what to do next, while the rational system is logical, analytical, deliberate, and methodical. Research in neuropsychology suggests that the...
6.4K
Inductive Reasoning00:59

Inductive Reasoning

60.4K
Inductive reasoning is a form of logical thinking that uses related observations to arrive at a general conclusion. It is uncertain and operates in degrees to which the conclusions are credible. As such, inductive arguments can be weak or strong, rather than valid or invalid, and conclusions can be used to formulate testable, falsifiable hypotheses.
Inductive reasoning is common in descriptive science. A life scientist makes observations and records them. This data can be qualitative or...
60.4K
Decision Making: P-value Method01:09

Decision Making: P-value Method

5.3K
The process of hypothesis testing based on the P-value method includes calculating the P- value using the sample data and interpreting it.
First, a specific claim about the population parameter is proposed. The claim is based on the research question and is stated in a simple form. Further, an opposing statement to the claim  is also stated. These statements can act as null and alternative hypotheses:  a null hypothesis would be a neutral statement while the alternative hypothesis can...
5.3K
Introduction to Cognitive Psychology01:20

Introduction to Cognitive Psychology

469
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...
469

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相关实验视频

Updated: Jun 25, 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

人类在循环中做了什么? 在使用机器学习驱动的决策辅助工具时,共同推理和实际判断.

Sabine Salloch1, Andreas Eriksen2

  • 1Hannover Medical School.

The American journal of bioethics : AJOB
|May 20, 2024
PubMed
概括

这项研究建议将患者视为"同事"和医疗保健中道德AI的认识系统合作伙伴. 它建议在评估机器学习驱动的决策支持系统时整合伦理原则,而不是权衡它们.

科学领域:

  • 医学伦理 医学伦理
  • 医疗保健中的人工智能
  • 机器学习伦理学 机器学习伦理学

背景情况:

  • 机器学习驱动的决策支持系统 (ML_CDSS) 的道德合法性通常依赖于"循环中的人类"或"有意义的人类控制"等概念.
  • 伦理原则通常被用作指导文件中的参考,需要平衡相互冲突的原则.

研究的目的:

  • 为ML_CDSS.提供"循环中的人类"概念的新解释.
  • 为评估医疗保健中的AI提供一个框架,超越了竞争的伦理原则的平衡.
  • 在人工智能驱动的医疗保健决策的背景下重新定义患者的角色.

主要方法:

  • 采用新坎蒂主义哲学观点,借鉴奥诺拉·奥尼尔 (Onora O'Neill) 的作品.
  • 分析患者在解释ML_CDSS的输出中的作用.
  • 开发一种替代方法,在AI评估中整合伦理原则.

主要成果:

  • 患者应该被视为"同事"和认识合作伙伴,以了解ML_CDSS的输出.
  • 基于伦理原则的整合方法比平衡方法更适合医疗AI评估.
  • 这种重构通过强调协作解释来支持道德合法性.
关键词:
临床决策支持系统 临床决策支持系统机器学习 机器学习伦理原则 伦理原则 伦理原则人在循环中的人类

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Assessment of Social Cognition in Non-human Primates Using a Network of Computerized Automated Learning Device ALDM Test Systems
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Last Updated: Jun 25, 2025

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结论:

  • 在医疗保健人工智能中",循环中的人类"应该被理解为一个积极的,认识的合作伙伴.
  • 整合伦理原则为评估医疗人工智能提供了比传统平衡行为更强大的方法.
  • 这种方法通过促进共享的理解和决策,提高了人工智能在医疗保健中的道德合法性.