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Uncertainty: Overview
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In analytical chemistry, we often perform repetitive measurements to detect and minimize inaccuracies caused by both determinate and indeterminate errors. Despite the cares we take, the presence of random errors means that repeated measurements almost never have exactly the same magnitude. The collective difference between these measurements - observed values - and the estimated or expected value is called uncertainty. Uncertainty is conventionally written after the estimated or expected value.
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Uncertainty: Confidence Intervals
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The confidence interval is the range of values around the mean that contains the true mean. It is expressed as a probability percentage. The interpretation of a 95% confidence interval, for instance, is that the statistician is 95% confident that the true mean falls within the interval. The upper and lower limits of this range are known as confidence limits. The confidence limits for the true mean are estimated from the sample's mean, the standard deviation, and the statistical factor...
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Propagation of Uncertainty from Systematic Error
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The atomic mass of an element varies due to the relative ratio of its isotopes. A sample's relative proportion of oxygen isotopes influences its average atomic mass. For instance, if we were to measure the atomic mass of oxygen from a sample, the mass would be a weighted average of the isotopic masses of oxygen in that sample. Since a single sample is not likely to perfectly reflect the true atomic mass of oxygen for all the molecules of oxygen on Earth, the mass we obtain from this...
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Propagation of Uncertainty from Random Error
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An experiment often consists of more than a single step. In this case, measurements at each step give rise to uncertainty. Because the measurements occur in successive steps, the uncertainty in one step necessarily contributes to that in the subsequent step. As we perform statistical analysis on these types of experiments, we must learn to account for the propagation of uncertainty from one step to the next. The propagation of uncertainty depends on the type of arithmetic operation performed on...
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Decision Making: P-value Method
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The process of hypothesis testing based on the P-value method includes calculating the P- value using the sample data and interpreting it.
First, a specific claim about the population parameter is proposed. The claim is based on the research question and is stated in a simple form. Further, an opposing statement to the claim is also stated. These statements can act as null and alternative hypotheses: a null hypothesis would be a neutral statement while the alternative hypothesis can...
First, a specific claim about the population parameter is proposed. The claim is based on the research question and is stated in a simple form. Further, an opposing statement to the claim is also stated. These statements can act as null and alternative hypotheses: a null hypothesis would be a neutral statement while the alternative hypothesis can...
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Documentation of Nursing Diagnosis
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The nurse documents nursing diagnoses and enters them into the patient record. The identified patient's nursing diagnosis is either written out with a plan of care or entered into the electronic health record.
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In some settings, data-driven computerized decision support systems are in place, allowing for more accurate nursing diagnoses. The database within one of these systems includes diagnostic labels defining characteristics, activities, and indicators for nursing. A nurse enters...
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对临床决策的解码不确定性
Krasimira Tsaneva-Atanasova1, Giulia Pederzanil2, Marianna Laviola3
1Department of Mathematics and Living Systems Institute, University of Exeter, Exeter, UK.
概括
不确定性量化 (UQ) 对可靠的临床决策至关重要. 解决数据不确定性可以改善医疗评估,从而改善患者的治疗结果.
科学领域:
- 医疗保健分析 医疗保健分析
- 医疗信息学 医疗信息学
- 临床决策支持 临床决策支持
背景情况:
- 临床决策依赖于数据,数据本身包含不确定性.
- 现有的医疗保健数据对采用UQ等先进分析方法提出了挑战和障碍.
- 了解和管理这些不确定性对于准确的医学评估至关重要.
研究的目的:
- 检查不确定性量化 (UQ) 在临床决策中的作用.
- 探索医疗保健数据的挑战和UQ采用的障碍.
- 突出UQ如何提高医学评估的准确性和可靠性.
主要方法:
- 这是一篇意见稿,讨论了UQ的概念框架和重要性.
- 分析医疗保健数据的挑战和UQ实施的潜在障碍.
- 审查UQ方法如何解决诊断工具和治疗结果的不确定性.
主要成果:
- UQ技术可以显著提高临床决策的准确性和稳定性.
- 对临床数据中的不确定性 (例如测量错误) 的系统分析是必不可少的.
- 有效的UQ带来了更好的患者结果和更明智的医疗保健实践.
结论:
- 不确定性量化对于可靠的临床决策至关重要.
- 克服UQ采用的障碍是为了推进医疗保健所必需的.
- 实施UQ提高了医疗评估和患者护理的准确性.


