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

Blood Studies for Cardiovascular System I: Cardiac Biomarkers01:20

Blood Studies for Cardiovascular System I: Cardiac Biomarkers

332
Cardiac biomarkers are enzymes, proteins, and hormones released into the blood when cardiac cells are injured. They are powerful tools for triaging.
The essential diagnostic tools for detecting myocardial necrosis and monitoring individuals suspected of having acute coronary syndrome (ACS) include:
Troponins
Troponins, particularly cardiac troponins I and T, are the most precise and sensitive markers of myocardial injury. They are detectable within 4-6 hours of myocardial injury and remain...
332
Cardiovascular Drugs: Classification based on Therapeutic Indications01:18

Cardiovascular Drugs: Classification based on Therapeutic Indications

3.2K
Cardiovascular diseases, encompassing a range of conditions, can significantly affect the heart's operations and the overall circulatory system. These conditions impair the heart's ability to pump blood, leading to a deficit in oxygen supply to crucial organs. Anomalies in the heart's electrical system, known as arrhythmias, can cause heartbeats to accelerate or slow down. Usually, heart rates increase during physical activity and decrease while resting or sleeping. However,...
3.2K

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

Link between physical activity, nutrition, and antimicrobial pharmacokinetics and therapeutic efficacy: Implications for resistance management.

SAGE open medicine·2026
Same author

Body fat estimation in the Mexican women's national soccer team: a cross-sectional agreement study between a derived Mexican Football Federation anthropometric equation and dual-energy X-ray absorptiometry.

Journal of the International Society of Sports Nutrition·2026
Same author

Cocoa-Based Plant Matrices in Glucose Metabolism: Bioactive Compounds and Redox Signaling.

Antioxidants (Basel, Switzerland)·2026
Same author

Physical Activity as a Mediator of the Relationship Between Mediterranean Diet Adherence and Anxiety Symptoms in Chilean Adolescents: A Cross-Sectional Study.

Children (Basel, Switzerland)·2026
Same author

Associations of Physical Fitness and Postural Balance with Psychosocial Well-Being in Early Adolescents: A School-Based Cross-Sectional Study.

Healthcare (Basel, Switzerland)·2026
Same author

Years of Experience and Its Association with Indicators of Adiposity and Health-Related Quality of Life in Teachers: A Cross-Sectional Study.

Healthcare (Basel, Switzerland)·2026
Same journal

Risk of Menstrual Dysfunction, Low Energy Availability, Eating Disorders and Injury in the First All-Female UK Military Team Rowing 3000 Miles Across the Atlantic.

Sports (Basel, Switzerland)·2026
Same journal

Phytotherapy in Sports Performance and Recovery: A Bibliometric Mapping of Research Themes and Trends.

Sports (Basel, Switzerland)·2026
Same journal

Competitive Stress Elicits Distinct Psychophysiological and Immunological Responses in Sub-Elite Water Polo Players.

Sports (Basel, Switzerland)·2026
Same journal

Multidimensional Predictors of Ranking-Based Competitive Success in National-Level Junior Tennis Players: Evidence for the Dominant Role of Physical Performance.

Sports (Basel, Switzerland)·2026
Same journal

Acute Moderate-Dose β-Alanine Improves Exercise Efficiency via Bicarbonate-Related Mechanisms During a Cycling Time Trial.

Sports (Basel, Switzerland)·2026
Same journal

Sustainable Athletes' Career Pathways and Mental Health Support: An Integrative Umbrella Review.

Sports (Basel, Switzerland)·2026
查看所有相关文章

相关实验视频

Updated: Sep 10, 2025

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

6.9K

基于健康状况的青少年心脏代谢风险分类的监督机器学习算法

Rodrigo Yáñez-Sepúlveda1, Rodrigo Olivares2, Pablo Olivares2

  • 1Faculty Education and Social Sciences, Universidad Andres Bello, Viña del Mar 2520000, Chile.

Sports (Basel, Switzerland)
|August 27, 2025
PubMed
概括
此摘要是机器生成的。

机器学习,特别是渐变增强,有效地使用体能测试对青少年的心脏代谢风险进行分类. 这种数据驱动的方法有助于早期发现和查年轻人.

关键词:
年轻人增强梯度健康问题身体健康预测模型

更多相关视频

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
12:18

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment

Published on: January 11, 2020

7.6K
Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
07:31

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack

Published on: May 15, 2020

7.2K

相关实验视频

Last Updated: Sep 10, 2025

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

6.9K
A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
12:18

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment

Published on: January 11, 2020

7.6K
Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
07:31

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack

Published on: May 15, 2020

7.2K

科学领域:

  • 公共卫生和预防医学
  • 计算生物学和生物信息学
  • 青少年健康与体育科学

背景情况:

  • 青少年心脏代谢风险是一个重要的公共卫生问题.
  • 身体健康是影响心脏代谢健康的关键可改变因素.
  • 传统的统计方法在健身和人体统计数据中存在复杂的关系.

研究的目的:

  • 开发和评估监督机器学习算法来分类青少年心脏代谢风险.
  • 用标准化的身体健康评估作为风险预测模型的输入.
  • 比较各种机器学习模型在识别有风险的青少年方面的表现.

主要方法:

  • 一个代表性学龄青少年样本的横截面分析.
  • 包括现场体能测试:心脏呼吸能力 (VO2max),肌肉力量 (俯仰) 和爆炸力 (水平跳跃).
  • 使用精度,F1分数,回忆和AUC-ROC指标的监督机器学习模型 (例如人工神经网络,集合方法) 的应用和比较.

主要成果:

  • 梯度提升分类器在测试模型中表现出卓越的性能.
  • 获得了77. 0%的准确性,67. 3%的F1分数,以及最高的AUC-ROC (0. 601),表明有效的风险分类.
  • 水平跳跃和俯卧运动被确定为心脏代谢风险的最重要的预测变量.

结论:

  • 渐变增强是利用身体健康数据预测青少年心脏代谢风险的一个非常有效的模型.
  • 这种机器学习方法为青少年早期风险检测提供了实用,数据驱动的工具.
  • 这些发现支持在教育和临床环境中可扩展的查计划的潜力.