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相关概念视频

Classification of Illness01:17

Classification of Illness

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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...
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COPD: Pathogenesis and Clinical Features01:20

COPD: Pathogenesis and Clinical Features

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Chronic obstructive pulmonary disease (COPD) is a group of lung conditions that progressively worsen over time, including chronic bronchitis and emphysema. This cluster of diseases collectively leads to a gradual and irreversible decline in lung function over time.
The primary cause for the onset of COPD is cigarette smoking and exposure to air pollution. These hazardous factors initiate a chain reaction within the lungs, resulting in chronic inflammation, damage to the airways, and a...
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Chronic Obstructive Pulmonary Disease01:22

Chronic Obstructive Pulmonary Disease

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COPD is defined as a heterogeneous lung condition marked by persistent respiratory symptoms such as dyspnea, cough, and sputum production, caused by abnormalities in the airways that cause airflow obstruction.
Smoking is a primary risk factor for COPD, with over 80% of patients having a history of it. Patients typically experience progressive dyspnea or labored breathing, frequent coughing, and recurrent pulmonary infections. Many eventually succumb to respiratory failure, characterized by...
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Common Respiratory Disorders01:31

Common Respiratory Disorders

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Respiratory disorders, a prevalent health concern globally, are generally divided into two primary categories: upper and lower respiratory tract disorders. The categorization is based on the area of the respiratory system they affect.
Upper respiratory disorders impact the airways above the vocal cords, encompassing areas like the nose, sinuses, and throat. Various conditions fall under this category, including the common cold and allergic rhinitis. These disorders can stem from several causes,...
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Chronic Obstructive Pulmonary Disease-IV: Assessement and Diagnostic Studies01:27

Chronic Obstructive Pulmonary Disease-IV: Assessement and Diagnostic Studies

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Assessing and diagnosing Chronic Obstructive Pulmonary Disease (COPD) involves a detailed approach that includes a comprehensive review of medical history, physical examination, and a variety of diagnostic tests. This thorough evaluation is essential to ensure an accurate diagnosis and guide effective management strategies.
Medical History
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Chronic Obstructive Pulmonary Disease-I: Introduction01:20

Chronic Obstructive Pulmonary Disease-I: Introduction

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Chronic Obstructive Pulmonary Disease (COPD) is a long-lasting respiratory condition requiring continuous attention and care. It is a progressive lung disease that leads to breathing challenges due to airflow obstruction. It manifests as persistent respiratory symptoms and restricted airflow resulting from abnormalities in the airways and alveoli, usually due to long-term exposure to harmful particles or gases. COPD mainly consists of two primary conditions: emphysema and chronic bronchitis.
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相关实验视频

Updated: Jul 25, 2025

Asthma Detection Research Based on Voice Signal Processing and Machine Learning
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优化的DEC:一个有效的咳检测框架,使用最佳加权的特征辅助深层集体分类器为COVID-19

Muhammad Awais1, Abhishek Bhuva2, Dipen Bhuva3

  • 1Department of Creative Technologies, Air University, Islamabad, Pakistan.

Biomedical signal processing and control
|June 26, 2023
PubMed
概括

这项研究引入了一种新的深度学习模型,使用咳音频信号检测COVID-19. 该模型实现了高准确度和精度,为早期疾病诊断提供了更快的替代方案.

关键词:
2019年新冠病毒疾病的流行情况咳音频信号 咳音频信号经验平均曲线分解修改过的基于猫和小鼠的优化器选择最佳权重特征选择优化了深层集体分类器.

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Lung CT Segmentation to Identify Consolidations and Ground Glass Areas for Quantitative Assesment of SARS-CoV Pneumonia
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科学领域:

  • 医疗信息学 医疗信息学
  • 人工智能的人工智能
  • 信号处理 信号处理

背景情况:

  • 由于症状的变化和现有方法的长时间处理,COVID-19的诊断具有挑战性.
  • 咳音频信号为早期COVID-19检测提供了一个有希望的,非侵入性的生物标志物.
  • 开发高效和准确的查工具对于流行病管理至关重要.

研究的目的:

  • 提出一种基于集体的新型深度学习模型,用于使用咳音频信号准确检测COVID-19.
  • 通过克服当前方法的局限性,加强早期查和诊断.
  • 调查结合信号分解,特征提取和优化深度学习分类器的有效性.

主要方法:

  • 咳音频信号使用实证平均曲线分解 (EMCD) 进行了分解.
  • 提取的特征包括Mel频率 Cepstral 系数 (MFCC),光谱和统计特征.
  • 使用修改后的基于猫和鼠标的优化器 (MCMBO) 来优化特征加权和深集群分类器 (ODEC) 参数,该分类器集成了辐射基函数 (RBF),长短期记忆 (LSTM) 和深度神经网络 (DNN) 分类器.

主要成果:

  • 拟议的模型实现了96%的准确性和92%的精度.
  • 使用MCMBO的功能融合和优化显著提高了检测性能.
  • 优化深层组合分类器 (ODEC) 展示了强大的诊断能力.

结论:

  • 开发的深度学习模型有效地从咳音频信号中检测到COVID-19.
  • 这种方法为早期COVID-19查提供了快速而准确的方法.
  • 这些发现支持在临床实践中使用人工智能驱动的音频分析来诊断传染病.