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Titrimetric analysis in solution chemistry involves measuring the volume of solutions and is often called volumetric analysis. The standard solution of known concentration in the burette is called the titrant, whereas the solution of unknown concentration in the flask is called the analyte, or titrand. Titrimetric analyses can be classified into four types based on the reactions between the titrant and analyte.
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Isolated atoms have discrete energy levels that are well described by the Bohr model. And, it quantifies the energy of an electron in a hydrogen atom as En. Higher quantum numbers 'n' yield less negative, closer electron energy levels.
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相关实验视频

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机器学习驱动的ADHD分类:用VMD子频段分析探索药物效应

Ebru Aker1, Şerife Gengeç Benli2, Zeynep Ak1

  • 1Department of Biomedical Engineering, Graduate School of Natural and Applied Sciences, Erciyes University, Kayseri, Turkey.

Current computer-aided drug design
|January 23, 2026
PubMed
概括

这项研究使用静止状态fMRI数据上的变态分解 (VMD) 来准确地分类注意力缺陷多动症 (ADHD) 亚型并评估药物效应,提供客观的诊断工具.

关键词:
在ADHD的分类,ADHD的分类.这是ADHD的亚型.fMRI信号的分解机器学习是机器学习.药物使用药物使用.这些子频段为子频段.

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科学领域:

  • 神经成像是一种神经成像.
  • 计算神经科学是一种神经科学.
  • 医疗信息学 医疗信息学

背景情况:

  • 注意缺陷多动性障碍 (ADHD) 是一种常见的神经发育障碍.
  • 目前的ADHD诊断依赖于主观评估,需要客观的,数据驱动的方法.
  • 神经成像,特别是静止状态fMRI,提供了客观ADHD评估的潜力.

研究的目的:

  • 使用静止状态fMRI数据对ADHD亚型进行分类.
  • 评估药物对ADHD分类的影响.
  • 开发一种客观的,计算机辅助的ADHD诊断方法.

主要方法:

  • 分析了来自ADHD-200数据集的休息状态fMRI数据.
  • 功能性MRI信号被转换为1D,并使用变化模式分解 (VMD) 将其分解成子频段.
  • 使用支持矢量机器 (SVM),线性差异分析 (LDA) 和人工神经网络 (ANN) 提取和分类统计特征.

主要成果:

  • 从VMD衍生出来的特性显著提高了分类性能.
  • 达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达达.
  • 药物治疗与非药物治疗的ADHD分类准确率为79.63%,所有组三元分类的分类准确率为69.51%.

结论:

  • 基于VMD的方法有效地改善了ADHD亚型分类和药物效果评估.
  • 这种方法显示出作为ADHD诊断和治疗规划的客观工具的希望.
  • 由于ADHD神经成像数据的复杂性,对多类分类准确性提出了挑战.