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相关概念视频

z Scores and Area Under the Curve01:17

z Scores and Area Under the Curve

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z scores are the standardized values obtained after converting a normal distribution into a standard normal distribution. A z score is measured in units of the standard deviation. The z score tells you how many standard deviations the value x is above (to the right of) or below (to the left of) the mean, μ. Values of x that are larger than the mean have positive z scores, and values of x that are smaller than the mean have negative z scores. If x equals the mean, then x has a z score of...
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Normal Distribution01:11

Normal Distribution

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The normal, a continuous distribution, is the most important of all the distributions. Its graph is a bell-shaped symmetrical curve, which is observed in almost all disciplines. Some of these include psychology, business, economics, the sciences, nursing, and, of course, mathematics. Some instructors may use the normal distribution to help determine students’ grades. Most IQ scores are normally distributed. Often real-estate prices fit a normal distribution. The normal distribution is...
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Critical Values01:31

Critical Values

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A critical value is a definite value obtained from a particular probability distribution at a predecided confidence level (or a predecided significance level) for a given population parameter. The critical value provides demarcation that separates the sample statistics that are likely to occur from the ones that are unlikely to occur based on the given probability distribution and the population parameter to be estimated. The critical value for normal distribution is obtained from the z...
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相关实验视频

Updated: May 12, 2025

Establishing a Competing Risk Regression Nomogram Model for Survival Data
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一种计算正常组织并发症概率的新公式.

Tingting Cao1, Qingqing Yuan2, Zhitao Dai2

  • 1Tongji Hospital Tongji Medical College of Huazhong University of Science and Technology Wuhan China.

Precision radiation oncology
|May 8, 2025
PubMed
概括
此摘要是机器生成的。

一个新的公式在治疗规划中简化了正常组织并发症概率 (NTCP) 的计算. 这种基于等效均剂量 (EUD) 的模型提供了比现有方法更准确和更稳定的临床数据匹配.

关键词:
相当于统一剂量的一致剂量.在 LKB 模型中,正常组织的并发症.

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科学领域:

  • 辐射瘤学 辐射瘤学
  • 生物物理学的生物物理.
  • 医学物理 医学物理

背景情况:

  • 对生物效应的定量建模对于有效的治疗规划至关重要.
  • 准确计算正常组织并发症概率 (NTCP) 对于最大限度地降低治疗毒性至关重要.
  • 现有的模型,比如莱曼-库彻-伯曼 (LKB) 公式,对于直接应用而言可能是复杂的.

研究的目的:

  • 开发一个简化的等效函数来计算NTCP的莱曼公式.
  • 促进定量生物建模在放射治疗治疗规划中的整合.
  • 引入一个新的NTCP模型,基于等效统一剂量 (EUD).

主要方法:

  • 莱曼-库彻-伯曼 (LKB) 公式的近似计算,使用三个参数 (n,m,TD50) 作为等效均剂量 (EUD) 的函数.
  • 在LKB模型参数方面数学推导和定义新的公式参数.
  • 用拟议的公式将参数重新校准到现有公差数据上.

主要成果:

  • 与LKB模型相比,开发了一种新的西格形NTCP公式,对称于TD50,与LKB模型相比差异很小 (<0.1%).
  • 导出的参数 (n,m,TD50) 在数学上是可靠的,并为重新校准的公差数据提供了更好的匹配.
  • 新模型表明,与LKB模型相比,大脑数据具有可比性或改进的拟合性.

结论:

  • 一种代表NTCP作为EUD的函数的新公式已经成功开发出来.
  • 导出的参数在数学上是合理的,并提供了增强的数据拟合能力.
  • 这种简化模型对治疗计划有潜在的用处,并且在脑数据上表现出强的表现.