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相关概念视频

Reasoning01:30

Reasoning

98
Reasoning is the action of thinking about something in a logical, sensible way. It is integral to problem-solving, decision-making, and critical thinking. Reasoning can be inductive or deductive. Reasoning involves transforming information into conclusions, which is essential for problem-solving, decision-making, and critical thinking.
Inductive reasoning involves deriving generalizations from specific observations. This type of reasoning helps form beliefs about the world. For example,...
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Reason and Intuition01:37

Reason and Intuition

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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...
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Critical Thinking II01:25

Critical Thinking II

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Critical thinking is a cognitive process with several attributes. The attributes of critical thinking include the following:
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Deductive Reasoning01:16

Deductive Reasoning

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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...
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Decision Making: Traditional Method01:14

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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...
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Decision Making01:20

Decision Making

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Decision-making is a fundamental cognitive process that involves evaluating alternatives and selecting among them. This process can range from simple choices, such as deciding what to wear, to complex decisions, like choosing a major in college or a career path. The complexity of the decision often dictates the approach we use, which can be broadly categorized into two types: automatic and controlled decision-making.
Automatic decision-making is fast, intuitive, and relies on gut feelings...
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相关实验视频

Updated: Jul 17, 2025

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
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基于知识图的可解释和个性化的认知推理模型:通用实践决策的方向

Qianghua Liu, Yu Tian, Tianshu Zhou

    IEEE journal of biomedical and health informatics
    |September 5, 2023
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    概括

    这项研究引入了一种新的可解释的人工智能模型,用于在初级卫生保健中诊断疾病. 基于知识图的认知推理模型提高了诊断准确度,并有助于临床决策.

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    科学领域:

    • 人工智能的人工智能
    • 医疗信息学 医疗信息学
    • 认知科学 认知科学

    背景情况:

    • 初级卫生保健 (PHC) 的质量,特别是在中国,需要提高诊断准确度.
    • 现有的人工智能 (AI) 工具用于临床决策支持缺乏可扩展性和可解释性.
    • 一般实践在很大程度上依赖于准确的诊断和治疗,以获得有效的患者护理.

    研究的目的:

    • 为一般实践决策提出基于知识图 (CRKG) 的可解释和个性化的认知推理模型.
    • 通过使用电子健康记录 (EHR) 提高疾病诊断的准确性和可解释性.
    • 在临床诊断中模拟人类认知过程.

    主要方法:

    • 构建一个半自动化腹部疾病知识图.
    • 开发CRKG模型,结合双过程理论,图形神经网络和注意力机制.
    • 使用EHR和知识图表进行个性化诊断和推理.

    主要成果:

    • 与基线方法相比,CRKG模型在疾病诊断中取得了更高的性能.
    • 获得了0.7873的精度@1,0.9020的召回@10和0.9340的命中@10用于腹部疾病诊断.
    • 对推理过程的可视化改善了临床医生的理解和模型可解释性.

    结论:

    • CRKG模型为改善一般实践中的诊断准确性和决策支持提供了一个有希望的方法.
    • 与知识图集集成的可解释人工智能可以显著提高在临床环境中电子健康记录的应用.
    • 这项研究推动了智能系统的开发,以实现个性化和可解释的医学诊断.