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相关概念视频

Machines01:19

Machines

576
Machines are complex structures consisting of movable, pin-connected multi-force members that work together to transmit forces. One example of a machine is the cutting plier, which is used to cut wires by applying forces to its handles. When equal and opposite forces are exerted on the handles of the cutting plier, they cause the cutting edges to come together and apply equal and opposite reaction forces on the wire, which are greater than the applied forces.
A free-body diagram of the...
576
Relative Risk01:12

Relative Risk

2.1K
Relative risk (RR) is a statistical measure commonly used in epidemiology to compare the likelihood of a particular event occurring between two groups. This metric is important for evaluating the relationship between exposure to a specific risk factor and the probability of a particular outcome. It plays a crucial role in medical research, public health studies, and risk assessment. Relative risk quantifies how much more (or less) likely an event is to occur in an exposed group compared to an...
2.1K
Machines: Problem Solving II01:30

Machines: Problem Solving II

663
Machines are complex structures consisting of movable, pin-connected multi-force members that work together to transmit forces. Consider a lifting tong carrying a 100 kg load. It comprises movable sections DAF and CBG linked together with member AB.
663
Machines: Problem Solving I01:22

Machines: Problem Solving I

711
A toggle clamp is a mechanical device commonly used for holding and clamping objects in various applications, such as woodworking, metalworking, and assembly operations. Consider a toggle clamp subjected to a force of 200 N at the handle. The vertical clamping force can be calculated, provided the dimensions of the toggle clamp are known.
The toggle clamp system is a machine structure consisting of movable, pin-connected multi-force members that form a stabilized system to transmit forces. The...
711
Avoidance Learning and Learned Helplessness01:14

Avoidance Learning and Learned Helplessness

2.6K
Avoidance learning and learned helplessness are critical concepts in understanding behavioral responses to negative stimuli.
Avoidance learning occurs when an organism learns that a specific behavior can prevent an unpleasant outcome. For example, a student who receives a bad grade may start studying harder to avoid future poor grades. This behavior persists even when the negative outcome is no longer present. Avoidance learning is powerful because it maintains behavior in the absence of the...
2.6K
Factors Affecting the Risk of Infection01:26

Factors Affecting the Risk of Infection

13.4K
The hosts' susceptibility to infection depends on several factors. The integrity of the skin and mucous membranes helps protect the body against microbial attacks. When the skin is altered, the chance of infection, limb loss, and even death increases.
The integrity and count of the white blood cells help the body resist pathogens and fight infection. When impaired, it reduces the body's resistance to pathogens. The acidic pH levels of the gastrointestinal, genitourinary tracts, and skin...
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相关实验视频

Updated: Jan 29, 2026

Multimodal Protocol for Assessing Metacognition and Self-Regulation in Adults with Learning Difficulties
12:55

Multimodal Protocol for Assessing Metacognition and Self-Regulation in Adults with Learning Difficulties

Published on: September 27, 2020

9.0K

使用六种机器学习方法,构建美国成年人注意力困难的风险屏幕.

Ying Song1, Yansun Sun2, Zedan Guo1

  • 1Department of Neurology, Peking University Shenzhen Hospital, Shenzhen, China.

Frontiers in artificial intelligence
|January 28, 2026
PubMed
概括
此摘要是机器生成的。

研究人员开发了一种机器学习模型,以识别美国成年人注意力集中障碍的风险因素. 后勤回归在预测度问题方面显示出最高的临床价值,有助于管理策略.

关键词:
尼汉斯 (NHANES) 是一个名人.难以集中注意力 难以集中注意力逻辑回归的逻辑回归方法机器学习是机器学习.神经精神疾病:神经精神疾病.

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Constructing and Visualizing Models using Mime-based Machine-learning Framework

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A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
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A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment

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相关实验视频

Last Updated: Jan 29, 2026

Multimodal Protocol for Assessing Metacognition and Self-Regulation in Adults with Learning Difficulties
12:55

Multimodal Protocol for Assessing Metacognition and Self-Regulation in Adults with Learning Difficulties

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Constructing and Visualizing Models using Mime-based Machine-learning Framework
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A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
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A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment

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科学领域:

  • 神经科学是一个神经科学.
  • 精神病学是一个精神病学.
  • 数据科学数据科学数据科学

背景情况:

  • 难以集中注意力是许多神经和神经精神疾病的关键症状.
  • 对于度困难的流行病学风险因素尚不清楚.

研究的目的:

  • 创建一个可解释的机器学习模型,用于预测美国成年人的注意力困难风险因素.
  • 通过使用先进的分析方法,识别集中困难的关键预测因素.

主要方法:

  • 利用了2015-2016年国家健康和营养检查调查 (NHANES) 中9,971名参与者的数据.
  • 应用并比较了六种机器学习算法:物流回归,ExtraTrees,包装,梯度提升,XGBoost和随机森林.
  • 使用AUC,准确性,精度,特异性,DCA和校准图表评估模型性能,从最佳模型构建一个名ogram.

主要成果:

  • 逻辑回归显示出优异的预测性能,AUC为0.881 (内部) 和0.818 (外部).
  • 决策曲线分析表明,逻辑回归在内部队列中提供了最大的净收益.
  • 随机森林在特定值 (0.2-0.3) 的外部队列中提供了最大的净收益.

结论:

  • 后勤回归是一种非常有价值的工具,用于预测专注困难.
  • 研究结果为识别,管理和开发集中障碍干预策略提供了关键的见解.