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相关概念视频

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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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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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Radiological investigations, including X-rays and computed tomography (CT) scans, are critical for diagnosing and evaluating various medical conditions. These imaging techniques provide valuable insights into the body's internal structures, aiding in the detection of abnormalities, assessment of disease progression, and development of treatment strategies. This article delves into two primary radiological investigations, chest X-rays and CT scans, outlining their purpose, procedures, and...
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相关实验视频

Updated: Mar 15, 2026

Guidelines and Experience Using Imaging Biomarker Explorer IBEX for Radiomics
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为瘤学解码不确定性量化-使用放射学图案的插图.

Florian van Daalen1, Balu Krishna Sasidharan2, C Praveenraj2

  • 1Department of Health Promotion, Care and Public Health Research Institute (CAPHRI), Maastricht University, 6211 LK Maastricht, The Netherlands.

Diagnostics (Basel, Switzerland)
|March 14, 2026
PubMed
概括
此摘要是机器生成的。

本研究介绍了瘤学中人工智能 (AI) 模型的不确定性量化 (UQ). UQ帮助临床医生了解AI预测可靠性,提高放射科医生和瘤学家的诊断信心.

关键词:
化剂的化剂认识论上的认识论.无线电学 (radiomics) 是一种无线电学.胸膜上皮瘤 胸膜上皮瘤不确定性量化不确定性量化

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科学领域:

  • 在瘤学瘤学.
  • 人工智能的人工智能
  • 医疗成像医学成像

背景情况:

  • 瘤学中的人工智能 (AI) 模型往往优先考虑准确性而不是确定性通信.
  • 人工智能预测中缺乏确定性评估,阻碍了瘤学家和放射学家的临床决策.

研究的目的:

  • 在瘤学中引入AI模型的不确定性量化 (UQ).
  • 为了提高放射科医生和瘤学家对AI预测可靠性的理解.
  • 通过更好的AI评估来改善临床决策.

主要方法:

  • 开发了一种用于胸膜上皮瘤的放射学风险模型 (RM).
  • 在特征空间内利用距离测量来量化AI模型的不确定性.
  • 分析了示例案例,以确定不确定性的可能原因.

主要成果:

  • 展示了一种用于测量AI模型中不确定性的方法.
  • 提供了一个框架来评估个人患者数据如何与培训套件保持一致.
  • 确定了临床医生可能需要用于AI驱动评估的额外信息的特定领域.

结论:

  • 将UQ集成到AI模型中可以提高预测可靠性的解释性.
  • UQ使临床医生能够通过了解AI评估信心来做出更明智的决策.
  • 进一步开发UQ方法对于在临床诊断中强大的AI整合至关重要.