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Improving Translational Accuracy02:07

Improving Translational Accuracy

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Base complementarity between the three base pairs of mRNA codon and the tRNA anticodon is not a failsafe mechanism. Inaccuracies can range from a single mismatch to no correct base pairing at all. The free energy difference between the correct and nearly correct base pairs can be as small as 3 kcal/ mol. With complementarity being the only proofreading step, the estimated error frequency would be one wrong amino acid in every 100 amino acids incorporated. However, error frequencies observed in...
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Guidelines and Experience Using Imaging Biomarker Explorer IBEX for Radiomics
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在放射学中重新思考特征可复制性:黑暗中的大象

Aydin Demircioğlu1

  • 1Institute of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, Essen, Germany. aydin.demircioglu@uk-essen.de.

European radiology experimental
|September 4, 2025
PubMed
概括

放射学研究应该优先考虑预测而不是特征重现. 即使是不可复制的特征也可以增强预测模型,挑战临床应用中的传统假设.

科学领域:

  • 医学成像分析
  • 放射学和定量成像
  • 生物医学数据科学

背景情况:

  • 放射学特征通常预计可用于临床预测模型的开发.
  • 复制性通常被认为是先决条件,可能会忽视有价值的预测信息.

研究的目的:

  • 调查不可重现的放射学特征对预测模型性能的影响.
  • 挑战在放射学中对特征重复性的传统强调.

主要方法:

  • 进行模拟试验重复试验以评估特征的可重复性.
  • 预测模型在包含不可重复的特征和不包含它们的情况下进行了评估.

主要成果:

  • 非可重现的特征对预测性表现作出了重大贡献.
  • 排除不可复制的特征导致模型精度下降.
  • 发现特征相互作用对于预测能力至关重要.

结论:

  • 在放射学中严格强调特征可重复性可能是不理想的.
  • 放射学模型应考虑特征相互作用,并优先考虑临床预测.
  • 不能重现的特征可以具有重要的预测价值.
关键词:
生物标志物机器学习辐射学结果的可复制性样本的大小

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