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相关概念视频

Prediction Intervals01:03

Prediction Intervals

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The interval estimate of any variable is known as the prediction interval. It helps decide if a point estimate is dependable.
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y. 
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Neural Control of Respiration01:18

Neural Control of Respiration

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The neural regulation of respiration is a meticulously coordinated process primarily controlled by the respiratory centers located within the brainstem. These centers, composed of specialized neurons, transmit nerve impulses that control the contraction and relaxation of our respiratory muscles.
Respiratory Centers in the Brainstem
Two primary areas comprise the respiratory center: the medullary respiratory center in the medulla oblongata and the pontine respiratory group in the pons. The...
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相关实验视频

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使用扩展卷积神经网络的COVID-19疾病预测基于征收飞行礼服队伍优化

Deepak Dahiya1

  • 1Computer Science (Tenure Stream), School of Engineering and Computer Science, University of Pittsburgh, Johnstown US.

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|June 26, 2023
PubMed
概括

这项研究引入了一种新的深度学习方法,用于使用CT扫描进行早期COVID-19检测. 这种方法提高了诊断的准确性,有助于在疫情期间及时照顾患者.

科学领域:

  • 医疗成像医学成像
  • 人工智能的人工智能
  • 计算生物学 计算生物学

背景情况:

  • COVID-19 流行病在全球范围内造成了广泛的健康危机.
  • 早期诊断COVID-19对于有效治疗和患者的治疗结果至关重要.
  • 深度学习在加速诊断程序方面提供了有希望的进展.

研究的目的:

  • 提出一种基于深度学习的新技术,用于早期检测COVID-19.
  • 通过医学成像来提高COVID-19诊断的准确性.

主要方法:

  • 对收集的CT图像应用高斯过器.
  • 使用一个状扩展卷积神经网络进行图像分析.
  • 优化深度学习的超参数,采用基于飞行的形行为算法.
  • 将图像分类为COVID-19阳性或阴性.

主要成果:

  • 拟议的深度学习方法在COVID-19诊断研究中表现出卓越的表现.
  • 评估指标证实了新方法的有效性.
  • 该技术成功地将COVID-19和非COVID-19病例分类,准确度提高.
关键词:
扩展的卷积卷积.全球聚合集团全球聚合集团这是一次重型飞行.神经网络的神经网络突尼卡特群群优化 群群优化

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结论:

  • 开发的深度学习技术显示了准确和早期检测COVID-19的巨大潜力.
  • 这种方法可以帮助医疗保健专业人员管理大流行.
  • 进一步的研究和验证对于临床实施是有必要的.