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Evolutionary Relationships through Genome Comparisons02:54

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Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...
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使用进化算法对冠状动脉狭窄的自动分类进行高维特征选择.

Miguel-Angel Gil-Rios1, Ivan Cruz-Aceves2, Arturo Hernandez-Aguirre3

  • 1Tecnologías de Información, Universidad Tecnológica de León, Blvd. Universidad Tecnológica 225, Col. San Carlos, León 37670, Mexico.

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概括
此摘要是机器生成的。

本研究介绍了一种高维特征选择的进化算法,用于分类冠状动脉狭窄. 一个由四个特征组成的子集实现了99%的歧视,使得临床决策支持的准确分类成为可能.

关键词:
K-最近的邻居功能银行 功能银行冠状动脉动脉图 (CAN) 是指冠状动脉动脉图.进化算法是一种进化算法.功能选择 功能选择狭窄症的分类 狭窄症的分类

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科学领域:

  • 医疗成像医学成像
  • 计算生物学 计算生物学
  • 机器学习 机器学习

背景情况:

  • 冠状动脉狭窄症的分类对于心血管疾病管理至关重要.
  • 高维特征选择在医学图像分析中构成了重大挑战.
  • 现有的方法难以应对自动冠状动脉狭窄检测的复杂性.

研究的目的:

  • 开发一种新的进化算法,用于冠状动脉狭窄症分类中的高维特征选择.
  • 为了确定最小但有效的特征子集,以准确检测疾病.
  • 根据最先进的技术来评估拟议的方法.

主要方法:

  • 一个特征提取阶段产生了473个特征 (强度,纹理,形状).
  • 一个进化算法在高维特征库 (O(2^473) 搜索空间上进行了特征选择.
  • 一个支持矢量机 (SVM) 分类器被训练并使用所选特征子集进行验证.

主要成果:

  • 一个由四个特征组成的子集实现了99%的歧视率.
  • 这四个特征的子集产生了高的分类性能:主要数据集的准确度为0.86和0.75的贾卡德系数.
  • 在一个更大的公共数据集 (2788个实例) 上,该方法实现了0.89准确度和0.80雅卡德系数.

结论:

  • 拟议的进化特征选择策略有效地识别了冠状动脉狭窄症的一小部分歧视性特征.
  • 识别的四个特征子集显示了高分类性能,适合临床决策支持系统.
  • 这种方法为冠状动脉疾病的自动和准确诊断提供了一个有希望的途径.