相关实验视频
Updated: Sep 12, 2026

13:19
Deep Neural Networks for Image-Based Dietary Assessment
Published on: March 13, 2021
9.3K
对深度学习自动轮中人口偏差风险的调查
Yasmin McQuinlan1, Charlotte L Brouwer2, Zhixiong Lin3
1Mirada Medical Ltd, Oxford, United Kingdom.
概括
基于深度学习的自动轮 (DLC) 性能不受地理人口的显著影响,尽管观察者感知偏差在临床可接受性中起着更大的作用.
科学领域:
- 医疗成像医学成像
- 人工智能的人工智能
- 辐射疗法 辐射疗法
背景情况:
- 基于深度学习的自动轮 (DLC) 算法通常使用来自单个地理群体的数据.
- 这可以在算法性能中引入基于人口的偏见.
研究的目的:
- 评估DLC算法中基于人口的偏差风险.
- 为了确定地理人口是否影响自动轮系统的性能.
主要方法:
- 分析了来自欧洲和亚洲诊所的80张头CT扫描.
- 在欧洲数据上训练的DLC解决方案与手动划线进行了比较.
- 量化措施和盲目的主观评估评估了绩效和可接受性.
主要成果:
- 两组之间观察到器官体积和定量相似度的显著差异.
- 定性评估显示,由于感知偏差而导致观察者接受的差异比地理来源更大.
- 韩国观察员对轮的接受度更高.
结论:
- 定量性能差异可能受到器官体积变化和小样本大小的影响.
- 观察者感知偏差显著影响自轮的临床可接受性.
- 未来的研究应该调查更多多样化的患者群体和解剖区域的地理偏见.
相关概念视频
Regression Toward the Mean
Regression toward the mean (“RTM”) is a phenomenon in which extremely high or low values—for example, and individual’s blood pressure at a particular moment—appear closer to a group’s average upon remeasuring. Although this statistical peculiarity is the result of random error and chance, it has been problematic across various medical, scientific, financial and psychological applications. In particular, RTM, if not taken into account, can interfere when researchers try to extrapolate results...
Random Sampling Method
Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. Data are the result of sampling from a population. The sampling method ensures that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest. Among the various sampling methods used by...
Estimating Population Mean with Known Standard Deviation
To construct a confidence interval for a single unknown population mean μ, where the population standard deviation is known, we need sample mean as an estimate for μ and we need the margin of error. Here, the margin of error (EBM) is called the error bound for a population mean (abbreviated EBM). The sample mean is the point estimate of the unknown population mean μ.
The confidence interval estimate will have the form as follows:
(point estimate - error bound, point estimate + error bound)
The...
The confidence interval estimate will have the form as follows:
(point estimate - error bound, point estimate + error bound)
The...
Estimating Population Standard Deviation
When the population standard deviation is unknown and the sample size is large, the sample standard deviation s is commonly used as a point estimate of σ. However, it can sometimes under or overestimate the population standard deviation. To overcome this drawback, confidence intervals are determined to estimate population parameters and eliminate any calculation bias accurately. However, this only applies to random samples from normally distributed populations. Knowing the sample mean and...
Estimating Population Mean with Unknown Standard Deviation
In practice, we rarely know the population standard deviation. In the past, when the sample size was large, this did not present a problem to statisticians. They used the sample standard deviation s as an estimate for σ and proceeded as before to calculate a confidence interval with close enough results. However, statisticians ran into problems when the sample size was small. A small sample size caused inaccuracies in the confidence interval.
William S. Gosset (1876–1937) of the Guinness...
William S. Gosset (1876–1937) of the Guinness...
Bias
Bias refers to any tendency that prevents a question from being considered unprejudiced. In research, bias occurs when one outcome or answer is selected or encouraged over others in sampling or testing. Bias can occur during any research phase, including study design, data collection, analysis, and publication.
In statistics, a sampling bias is created when a sample is collected from a population, and some members of the population are not as likely to be chosen as others (remember, each member...
In statistics, a sampling bias is created when a sample is collected from a population, and some members of the population are not as likely to be chosen as others (remember, each member...

