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

103
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...
103
Electrocardiogram01:29

Electrocardiogram

2.2K
An electrocardiogram (ECG or EKG) is a critical diagnostic tool that records the electrical signals produced by the heart during each heartbeat. This recording is achieved through electrodes placed strategically on the arms, legs, and chest. The electrocardiograph amplifies these signals and produces 12 distinct tracings, offering a comprehensive understanding of the heart's electrical activity.
Three major waveforms are present in a typical ECG recording: the P wave, the QRS complex, and...
2.2K
Acute Coronary Syndrome III: Diagnostic studies01:30

Acute Coronary Syndrome III: Diagnostic studies

3
Diagnosing acute coronary syndrome or ACS begins with a thorough patient history. Notable symptoms include central, crushing chest pain radiating to the left arm, neck, jaw, or back, along with shortness of breath, sweating (diaphoresis), nausea, vomiting, dizziness, and palpitations.It is crucial to note any history of cardiac illnesses and assess risk factors, including age, gender, smoking, hypertension, diabetes, hyperlipidemia, and a sedentary lifestyle.During physical examination, vital...
3
Holter Monitor: 24-Hour Monitoring01:23

Holter Monitor: 24-Hour Monitoring

3
Holter monitoring is a continuous electrocardiography (ECG) recording that tracks the heart's electrical activity over an extended period, generally 24 to 48 hours. This noninvasive diagnostic tool detects irregular heart rhythms that may not be captured during a standard ECG performed in a clinical setting.DeviceThe Holter monitor is a portable, small device connected to several electrodes on the patient's chest. These electrodes detect the heart's electrical signals and transmit them to the...
3

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

Long-term follow-up of cognitive behavior therapy for obsessive-compulsive disorder in adults and children: a systematic review and meta-analysis.

Cognitive behaviour therapy·2026
Same author

Pediatric In-Hospital Cardiac Arrest in Sweden: A Tertiary Care Cohort With High Survival.

Acta anaesthesiologica Scandinavica·2026
Same author

Associations between prediabetes, type 2 diabetes and incident atrial fibrillation in patients with hypertension: Results from the Swedish Primary Care Cardiovascular Database.

American journal of preventive cardiology·2026
Same author

Prediction of cardiac arrest in patients with heart failure in Sweden: a registry study with development of a machine learning model.

BMJ open·2026
Same author

Standardised, telemonitored titration of guideline-directed medical therapy in heart failure is associated with faster optimisation and improved persistence compared to standard of care.

Open heart·2026
Same author

Acute Myocardial Infarction versus Acute Decompensated Heart Failure in Cardiogenic Shock: A Systematic Review and Meta-Analysis of Clinical Phenotypes and Mortality.

European journal of heart failure·2026

相关实验视频

Updated: Jun 9, 2025

Using Extraordinary Optical Transmission to Quantify Cardiac Biomarkers in Human Serum
09:23

Using Extraordinary Optical Transmission to Quantify Cardiac Biomarkers in Human Serum

Published on: December 13, 2017

6.2K

使用深度神经网络从心电图中预测热素生物标志物升高.

Lukas Hilgendorf1,2, Petur Petursson3,4, Vibha Gupta3,2

  • 1Department of Molecular and Clinical Medicine, University of Gothenburg, Goteborg, Sweden lukas.hilgendorf@gu.se.

Open heart
|October 30, 2024
PubMed
概括

使用心电图 (ECG) 的深度学习模型可以预测胸痛患者的高托罗水平. 这种工具提供了高负预测准确度,有助于在紧急情况下快速分拣.

关键词:
急性冠状动脉综合征是什么胸部疼痛 胸部疼痛 胸部疼痛冠状动脉疾病冠状动脉疾病

更多相关视频

Electroencephalography Network Indices as Biomarkers of Upper Limb Impairment in Chronic Stroke
06:37

Electroencephalography Network Indices as Biomarkers of Upper Limb Impairment in Chronic Stroke

Published on: July 14, 2023

816
Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention
06:37

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Published on: December 15, 2023

2.6K

相关实验视频

Last Updated: Jun 9, 2025

Using Extraordinary Optical Transmission to Quantify Cardiac Biomarkers in Human Serum
09:23

Using Extraordinary Optical Transmission to Quantify Cardiac Biomarkers in Human Serum

Published on: December 13, 2017

6.2K
Electroencephalography Network Indices as Biomarkers of Upper Limb Impairment in Chronic Stroke
06:37

Electroencephalography Network Indices as Biomarkers of Upper Limb Impairment in Chronic Stroke

Published on: July 14, 2023

816
Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention
06:37

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Published on: December 15, 2023

2.6K

科学领域:

  • 心脏病学 心脏病学
  • 人工智能的人工智能
  • 医学诊断 医学诊断 医学诊断

背景情况:

  • 升高的托罗邦素水平表明心脏损伤.
  • 电心电图 (ECG) 在紧急情况下很容易获得.
  • 从心电图中预测热素升高可以加快患者的护理.

研究的目的:

  • 开发和评估一个深度学习模型来预测热素升高.
  • 评估ECG与人工智能结合用于心脏诊断的实用性.
  • 为急诊室决策提供一个节省时间的工具.

主要方法:

  • 一个残留卷积神经网络 (ResNet) 在15856个心电图上接受了训练,这些心电图来自胸痛或呼吸障碍患者.
  • 数据包括高灵敏度素测试结果 (素I和素T) 在ECG获取后6小时内.
  • 该模型经过训练和验证,使用多个数据分割来确保稳定性.

主要成果:

  • 在ResNet模型中,平均曲线下的面积 (AUC) 为0.7717.
  • 该模型的准确率为71.43%,F1得分为0.5642.
  • 观察到高负预测值 (NPV) 为0.8660,表明可靠的排除升高的热素.

结论:

  • 发达的神经网络在预测热素升高方面表现出临床上有意义的表现.
  • 该模型的高负预测精度使其成为排除心脏损伤的宝贵工具.
  • 这种人工智能驱动的方法可以作为一种有价值的选择,用于胸痛或呼吸不良的患者的第一线分拣.