Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Genome-wide Association Studies-GWAS01:11

Genome-wide Association Studies-GWAS

12.6K
Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
GWAS does not require the identification of the target gene involved in...
12.6K

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Large deviations of current for the symmetric simple exclusion process on a semi-infinite line and on an infinite line with a slow bond.

Physical review. E·2026
Same author

Roth spots: A clue to the diagnosis of infective endocarditis.

The National medical journal of India·2026
Same author

Lipid abnormalities in chronic viral hepatitis: associations and machine learning-enhanced prediction.

BMC gastroenterology·2026
Same author

Linking soil enzymes and microbial community dynamics with organic carbon fluctuations for sustaining the soil health.

Scientific reports·2026
Same author

Microencapsulation-Based Valorization of Galgal (Citrus pseudolimon L.) Peel Oil: Toward Sustainable Food Protection Solutions.

Chemistry & biodiversity·2026
Same author

Smart irrigation system and early plant disease detection using IoT and novel non-linear growing self-organizing map based artificial neural network.

Scientific reports·2026
Same journal

Application of ephrin-B2 loaded glycol chitosan-silk fibroin hydrogel in the treatment of diabetic refractory wounds.

Scientific reports·2026
Same journal

International expert Delphi consensus on thromboprophylaxis in metabolic and bariatric surgery.

Scientific reports·2026
Same journal

Assessing the cross-region knowledge transfer capability of selected deep learning building vectorization methods in the context of available training datasets.

Scientific reports·2026
Same journal

Feasibility and preliminary effects of outdoor versus indoor cognitive-motor therapy in women with Alzheimer's disease: A randomized single-blind pilot study.

Scientific reports·2026
Same journal

Hallmarks of social action in the vocal turn-taking of wild common marmosets (Callithrix jacchus).

Scientific reports·2026
Same journal

Role and mechanism of AOPPs-induced NOX4-mediated ferroptosis in intervertebral disc degeneration.

Scientific reports·2026
查看所有相关文章

相关实验视频

Updated: May 2, 2026

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns
13:44

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns

Published on: August 30, 2013

42.8K

通过改进的多目标WOA,有效的特征选择用于基因病理图像分类.

Ravi Sharma1, Kapil Sharma2, Manju Bala3

  • 1Delhi Technological University, Bawana, New Delhi, 110042, India. ravisrma1988@gmail.com.

Scientific reports
|October 25, 2024
PubMed
概括
此摘要是机器生成的。

本研究介绍了一种增强的多目标鱼优化算法,用于在组织病理学图像分析中高效的特征选择,提高准确性和减少与现有方法相比计算时间.

关键词:
图像的分类图像的分类.多目的灰狼优化器 多目的灰狼优化器优化算法优化算法在加工前进行预处理.

更多相关视频

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
07:35

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Published on: October 11, 2018

7.4K
Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model
07:15

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model

Published on: August 16, 2020

6.7K

相关实验视频

Last Updated: May 2, 2026

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns
13:44

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns

Published on: August 30, 2013

42.8K
Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
07:35

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Published on: October 11, 2018

7.4K
Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model
07:15

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model

Published on: August 16, 2020

6.7K

科学领域:

  • 计算病理学计算病理学
  • 生物信息学是一种生物信息学.
  • 机器学习是机器学习.

背景情况:

  • 高效的特征选择对于组织病理学图像分析至关重要,但仍然是一个挑战.
  • 当前的方法往往将特征选择视为一个单一目标的问题,从而限制了它们的有效性.

研究的目的:

  • 提出一个增强的多目标鱼优化算法 (EMOWOA) 用于特征选择在他的病理学.
  • 在复杂的图像分析任务中解决单一目标方法的局限性.

主要方法:

  • 开发并使用了一种增强的多目标鱼优化算法 (EMOWOA).
  • 在10个标准的多目标基准函数 (CEC2009) 上验证了EMOWOA.
  • 将EMOWOA与使用五个分类器的三种现有特征选择技术进行比较,评估准确性,选择的特征和计算时间.

主要成果:

  • 拟议的EMOWOA展示了对基准函数的卓越优化能力.
  • 在评估的参数 (准确性,特征数量,时间) 中,EMOWOA显著优于现有方法.
  • 该算法有效地挖掘了用于组织病理学图像分析的最佳特征集.

结论:

  • 增强的多目标鱼优化算法提供了一个强大的解决方案,用于有效的特征选择在他的病理学.
  • 这种方法改进了传统的单一目标方法,提供了更好的绩效指标.
  • 这些发现突出了多目标优化在推进计算病理学的潜力.