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

Parkinson's Disease: Treatment01:24

Parkinson's Disease: Treatment

295
Neurodegenerative disorders, such as Parkinson's Disease (PD), involve the gradual and irreversible destruction of neurons in particular brain areas. These disorders exhibit standard features like proteinopathies, selective vulnerability of some neurons, and an interaction of intrinsic properties, genetics, and environmental influences in neural injury.
Parkinson's Disease is primarily a result of the loss of dopaminergic neurons in the substantia nigra pars compacta. The cornerstone of...
295
Parkinson's Disease: Overview01:15

Parkinson's Disease: Overview

592
Neurodegenerative disorders are progressive diseases that cause irreversible damage and loss to neurons in specific brain areas. Examples of these disorders include Parkinson's disease, Alzheimer's disease, Multiple Sclerosis (MS), and Amyotrophic Lateral Sclerosis (ALS). These disorders share characteristics such as proteinopathies, selective neuronal vulnerability, and a complex interplay between genetic and environmental factors. The primary therapeutic goal for these conditions is...
592
Neural Regulation01:37

Neural Regulation

39.5K
Digestion begins with a cephalic phase that prepares the digestive system to receive food. When our brain processes visual or olfactory information about food, it triggers impulses in the cranial nerves innervating the salivary glands and stomach to prepare for food.
39.5K

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

Early detection of Alzheimer's disease using deep learning methods.

Alzheimer's & dementia : the journal of the Alzheimer's Association·2025
Same author

SMS Scam Detection Application Based on Optical Character Recognition for Image Data Using Unsupervised and Deep Semi-Supervised Learning.

Sensors (Basel, Switzerland)·2024
Same author

An Ensemble Machine Learning and Data Mining Approach to Enhance Stroke Prediction.

Bioengineering (Basel, Switzerland)·2024
Same author

Machine Learning-Based Predictive Models for Detection of Cardiovascular Diseases.

Diagnostics (Basel, Switzerland)·2024
Same author

Application of Machine Learning to Predict COVID-19 Spread via an Optimized BPSO Model.

Biomimetics (Basel, Switzerland)·2023
Same author

Empowering Precision Medicine: Unlocking Revolutionary Insights through Blockchain-Enabled Federated Learning and Electronic Medical Records.

Sensors (Basel, Switzerland)·2023

相关实验视频

Updated: Jul 16, 2025

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

7.5K

使用过特征选择和带有合奏学习的遗传算法检测帕金森病.

Abdullah Marish Ali1, Farsana Salim2, Faisal Saeed2

  • 1Department of Computer Science, Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah 21589, Saudi Arabia.

Diagnostics (Basel, Switzerland)
|September 9, 2023
PubMed
概括
此摘要是机器生成的。

这项研究表明,机器学习模型,特别是决策树和随机森林,可以使用语音数据准确检测帕金森病 (PD). 特征选择和组合方法进一步提高了这种神经退行性疾病的检测准确性.

关键词:
帕金森病 (PD) 是一种疾病.组合学习组合学习过器的功能选择的选择.遗传选择 遗传选择

更多相关视频

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

6.8K
Application of a C. elegans Dopamine Neuron Degeneration Assay for the Validation of Potential Parkinson's Disease Genes
08:42

Application of a C. elegans Dopamine Neuron Degeneration Assay for the Validation of Potential Parkinson's Disease Genes

Published on: July 18, 2008

16.1K

相关实验视频

Last Updated: Jul 16, 2025

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

7.5K
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

6.8K
Application of a C. elegans Dopamine Neuron Degeneration Assay for the Validation of Potential Parkinson's Disease Genes
08:42

Application of a C. elegans Dopamine Neuron Degeneration Assay for the Validation of Potential Parkinson's Disease Genes

Published on: July 18, 2008

16.1K

科学领域:

  • 计算神经科学是一种计算神经科学.
  • 医疗信息学医学信息学
  • 机器学习在医疗保健中的应用.

背景情况:

  • 帕金森病 (PD) 是一种进展性神经退行性疾病,影响运动和非运动功能,显著降低患者的生活质量.
  • 准确和早期发现PD对于有效的管理和治疗策略至关重要.
  • 语音分析为潜在的PD检测提供了一种非侵入性方法,原因是特征性的声音变化.

研究的目的:

  • 用语音数据调查波器特征选择,集体学习和基因选择在检测帕金森病时的有效性.
  • 在PD检测的不同数据集上比较各种分类模型的性能.
  • 评估特征选择和组合方法对PD患者鉴定准确性和精度的影响.

主要方法:

  • 利用了两个不同的数据集,包括PD患者和健康个体的语音特征.
  • 应用过器通过删除近乎恒定的特征来选择特征.
  • 测试并比较决策树,随机森林和XGBoost分类器的性能.
  • 实施集体学习方法 (投票,堆叠,包装) 以提高分类性能.
  • 使用遗传选择进行特征评估和随后的分类.

主要成果:

  • 在特征选择后,决策树和随机森林分类器在数据集1上实现了100%的准确性.
  • 研究了集体学习方法,以进一步优化高性能模型的性能.
  • 在大多数场景中,基因选择在识别PD患者方面表现出高精度,与健康个体相比.
  • 与数据集2相比,数据集1的分类性能优于数据集2,这可能是由于数据集2的特征集更大.

结论:

  • 机器学习,特别是优化的特征选择和组合技术,显示出从语音数据中准确检测帕金森病的巨大潜力.
  • 应用的方法,特别是过数据上的决策树和随机森林,为非侵入性PD诊断提供了一个有希望的途径.
  • 进一步的研究验证这些发现在不同的数据集是有必要的,以建立临床实用性.