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相关概念视频

Classification of Illness01:17

Classification of Illness

7.5K
The meaning of illness is individualized to each person who experiences an alteration in health. In contrast, disease is a medical term indicating a pathological change in the structure and function of the body or mind. It is a condition that has specific symptoms and boundaries.
An illness is a response to a disease in which the person's level of functioning is changed compared with a previous level. The general classification of illness includes acute and chronic.
Acute illness is severe...
7.5K
Heart Sounds01:15

Heart Sounds

1.9K
Heart sounds are generated by the turbulence in blood flow due to the closing of heart valves. These sounds are best perceived slightly away from the valves, where the blood flow disseminates the sound.
Auscultation is the process of listening to these internal body sounds using a stethoscope. The heart produces four types of sounds, but only two—S1 and S2—can usually be heard with a stethoscope.
S1, also known as the "lub" sound, is caused by the closure of atrioventricular (A-V)...
1.9K
Assessment of the Cardiovascular System IV: Auscultation01:25

Assessment of the Cardiovascular System IV: Auscultation

336
Cardiac auscultation is a clinical skill used to assess heart function and detect abnormalities. It involves listening to heart sounds at specific anatomical locations through a stethoscope.
Normal Heart Sounds
S1 (First Heart Sound)-
S1 is made by the closure of the mitral and tricuspid valves (atrioventricular valves), marking the beginning of systole.
S2 (Second Heart Sound)-
S2 is made by the closure of the aortic and pulmonic valves (semilunar valves), marking the end of the systole.
336
Imaging Studies for Cardiovascular System I:Echocardiography01:17

Imaging Studies for Cardiovascular System I:Echocardiography

333
Cardiac imaging studies encompass a wide range of noninvasive and minimally invasive techniques designed to visualize the heart's structure and function in detail. One such technique is echocardiography, which uses high-frequency ultrasound waves to produce detailed images of the heart, known as echocardiograms.
Indications: Echocardiography is utilized to diagnose heart failure, valve disorders, and myocardial infarction. It also assesses cardiac structures' size, shape, and motion,...
333
Cardiovascular System Abnormal Findings II: Auscultation01:25

Cardiovascular System Abnormal Findings II: Auscultation

150
Auscultation, an essential part of a heart examination, is done using a stethoscope. It provides crucial information about heart function and possible heart problems. Due to heart problems, abnormal sounds can be heard during systole or diastole. These sounds include S3 and S4 gallops, opening snaps, systolic clicks, and murmurs.
Abnormal Heart Sounds
Gallops:
150
Pulse rhythm01:30

Pulse rhythm

800
Pulse rhythm refers to the pattern of pulsations within specific intervals, offering valuable insights into the regularity or irregularity of the heart's beats as observed through the pattern of pulsation within specific intervals. A regular pulse exhibits a consistent heart rate with uniform waveforms and pulsation force, variations of which can be classified as normal, weak, or bounding.
Conversely, an irregular pulse pattern is termed dysrhythmia, stemming from disruptions in cardiac...
800

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相关实验视频

Updated: Jul 4, 2025

Semi-automated Optical Heartbeat Analysis of Small Hearts
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Semi-automated Optical Heartbeat Analysis of Small Hearts

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人工智能框架用于从音频信号进行心脏病分类.

Sidra Abbas1, Stephen Ojo2, Abdullah Al Hejaili3

  • 1Department of Computer Science, COMSATS University Islamabad, Islamabad, Pakistan. sidraabbas@ieee.org.

Scientific reports
|February 7, 2024
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概括

这项研究表明,机器学习 (ML) 和深度学习 (DL) 可以通过杂的音频信号来检测心脏病. 一个多层感知子模型实现了95.65%的准确性,改善了心血管诊断.

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Author Spotlight: Advancing the Study of Brain-Heart Interplay with a Comprehensive EEGLAB Plugin for Multimodal Signal Analysis
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Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention
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科学领域:

  • 心脏病学 心脏病学
  • 生物医学工程 生物医学工程
  • 数据科学数据科学数据科学

背景情况:

  • 心血管疾病是全球死亡的主要原因之一.
  • 对心脏病的准确和早期诊断对于有效的治疗和患者的结果至关重要.
  • 当前的诊断方法可能是侵入性的或需要专门的设备,从而产生了对可访问的替代品的需求.

研究的目的:

  • 研究机器学习 (ML) 和深度学习 (DL) 技术在使用音频声音信号检测心脏病方面的有效性.
  • 分析各种ML和DL模型在从心脏噪音录音中对心血管疾病进行分类方面的表现.
  • 探索数据增强和特征组合策略,以提高诊断准确度.

主要方法:

  • 利用来自帕斯卡挑战的两个实心音频数据集的子集.
  • 采用了信号可视化技术,包括光谱图和Mel频 Cepstral 系数 (MFCC).
  • 应用数据增强来引入合成噪声,并开发了一个功能组合器,用于集成的音频功能提取. 评估了几个ML和DL分类器.

主要成果:

  • 多层感知子模型在评估的分类器中表现出卓越的性能.
  • 性能最好的模型在通过音频信号检测心脏病时达到95.65%的准确率.
  • 信号处理技术和数据增强对模型的稳定性和准确性做出了重大贡献.

结论:

  • 使用ML和DL的基于音频信号的分析为心脏病检测提供了一个有希望的,非侵入性的方法.
  • 取得的高精度凸显了将这种方法纳入临床实践的潜力.
  • 这项研究为改善医疗诊断,增强患者护理和更容易获得的心血管查提供了机会.