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相关概念视频

Machines: Problem Solving I01:22

Machines: Problem Solving I

846
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...
846
Machines: Problem Solving II01:30

Machines: Problem Solving II

793
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.
793

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使用众包与机器学习融合的数字诊断多次发育延迟:人类在循环中的机器学习研究方案

Aditi Jaiswal1, Ruben Kruiper1, Abdur Rasool1

  • 1Department of Information and Computer Sciences, University of Hawaii at Manoa, Honolulu, HI, United States.

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概括

这项研究引入了一个游戏化的网络系统和机器学习 (ML) 来同时诊断未成年人的自闭症谱系障碍和注意力缺陷/多动症障碍,提高了儿科精神疾病的准确性.

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更多关于 ADHD ADHD 的文章在ASD中,使用的是ASD.注意力缺陷/多动症障碍.自闭症谱系障碍 自闭症谱系障碍众包 (crowdsourcing) 是一种众包方式.机器学习是机器学习.精确的健康健康的准确性

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科学领域:

  • 数字健康数字健康
  • 机器学习在儿科中的应用.
  • 行为科学是一种行为科学.

背景情况:

  • 由于成本,距离和临床医生的可用性,儿童精神疾病往往被诊断不足.
  • 目前用于儿科精神病的数字表型化工具在特征集和预测准确性方面存在局限性.
  • 现有的方法往往侧重于单一的二进制预测,导致诊断结果不确定.

研究的目的:

  • 开发一个游戏化的网络系统,用于自适应性数据收集.
  • 将新的众包算法与ML集成在一起,用于行为特征提取.
  • 同时准确地预测自闭症谱系障碍和注意力缺陷/多动症障碍.

主要方法:

  • 游戏化的网络应用程序以适应性地策划社交互动的视频.
  • 自动化ML方法和众包算法用于行为特征提取.
  • 基于数据不确定性的同时分类和适应性信息请求的ML模型.

主要成果:

  • 一个初步的Web界面已经开发出来.
  • 一种特征选择方法为游戏化方法确定了关键的行为特征.
  • 该系统旨在准确,同时预测多种条件.

结论:

  • 开发一种基于人工智能的工具来区分自闭症谱系障碍和注意力缺陷/多动障碍等疾病是一个重要的前景.
  • 这种方法有可能提高复杂儿科精神疾病的诊断准确性.
  • 该系统旨在解决目前未成年人诊断工具的局限性.