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Related Concept Videos

Asthma-I: Introduction01:29

Asthma-I: Introduction

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Asthma is a chronic respiratory ailment that requires careful management due to its varying symptoms and influencing factors. It is characterized by airway inflammation, bronchial hyperresponsiveness, and reversible airflow obstruction, leading to symptoms like wheezing, shortness of breath, chest tightness, and coughing. The symptom frequency and intensity may vary considerably over time. It is also linked to immune system responses to allergens and irritants, highlighting the complex...
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Asthma-IV: Diagnostic and Management01:30

Asthma-IV: Diagnostic and Management

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The diagnosis and management of asthma are comprehensive, encompassing clinical assessments, lung function tests, and pharmacological interventions. Here's an overview:
Clinical Assessment for Asthma:
This is the first step in diagnosing and managing asthma. It includes:
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Asthma: Pathogenesis and Management01:20

Asthma: Pathogenesis and Management

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Asthma is a chronic pulmonary condition involving inflammation of the airways, hyper-reactivity, and reversible obstruction of the airways. This condition can significantly impact a person's quality of life, making breathing difficult and leading to distressing symptoms.
Asthma is classified as allergic and non-allergic. Allergens such as dust mites, pollen, and pet dander trigger allergic asthma, while factors like cold air, intense emotions, or exercise can induce non-allergic asthma.
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Asthma-III: Symptoms and Complications01:24

Asthma-III: Symptoms and Complications

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Asthma, a common chronic respiratory condition, is classified considering the frequency and severity of symptoms alongside lung function impairment. Understanding this classification is essential for appropriate treatment and management. Here's a detailed look at the classification of asthma and its clinical features and complications:
Classification of Asthma
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Asthma-IV: Nursing Management01:30

Asthma-IV: Nursing Management

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The nursing management of asthma is a comprehensive approach that relies heavily on the expertise and dedication of healthcare professionals. It involves thorough assessment, accurate diagnosis, strategic planning, effective implementation, and diligent evaluation. By meticulously following this step-by-step process, healthcare professionals play a crucial role in providing the best possible care and treatment for patients with asthma, enhancing their overall health and well-being.
First, in...
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Asthma-II: Pathophysiology and Classification01:26

Asthma-II: Pathophysiology and Classification

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Asthma is a prevalent chronic respiratory condition marked by inflammation and hyperresponsiveness of the airways. Its pathophysiology involves complex interactions among inflammatory pathways, immune responses, and neural mechanisms.
Additionally, environmental and genetic factors play crucial roles in determining an individual's susceptibility to asthma and the severity of their condition.
Critical processes in asthma pathophysiology include:
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Related Experiment Video

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Asthma Detection Research Based on Voice Signal Processing and Machine Learning
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Artificial Intelligence in Asthma: Current Status, Opportunities, and Pitfalls.

Athena Gogali1, Christos Kyriakopoulos1, Dimitrios Potonos1

  • 1Respiratory Medicine Department, University of Ioannina, Ioannina, Greece.

The Journal of Allergy and Clinical Immunology. in Practice
|June 5, 2025
PubMed
Summary

Artificial intelligence (AI) and machine learning (ML) are revolutionizing asthma care by improving diagnosis, risk assessment, and personalized treatment. These technologies enhance clinical decisions, supporting physicians in managing this complex respiratory condition.

Keywords:
Artificial intelligenceAsthmaDeep learningDigital toolsMachine learning

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Area of Science:

  • Computational biology
  • Respiratory medicine
  • Artificial Intelligence

Background:

  • Asthma presents diagnostic and management challenges due to its complexity, diverse phenotypes/endotypes, and common treatment adherence issues.
  • Despite available treatments, effective asthma control remains difficult for many patients.
  • Advances in AI and ML offer new tools for improving medical decisions and patient outcomes.

Purpose of the Study:

  • To review recent literature (last 3 years) on the application of AI and ML in asthma.
  • To map current knowledge on AI/ML in asthma diagnosis, risk assessment, classification, and management.
  • To identify future research directions for AI/ML in precision asthma care.

Main Methods:

  • Narrative review of scientific literature published in the last three years.
  • Focus on studies integrating AI/ML techniques into various aspects of asthma care.
  • Analysis of applications in risk identification, screening, diagnosis, classification, exacerbation prediction, and guided treatment.

Main Results:

  • AI/ML show significant promise in enhancing asthma diagnosis, classification, and risk prediction by analyzing large datasets.
  • Applications span early diagnosis, personalized treatment strategies, and exacerbation prevention.
  • AI/ML tools are increasingly integrated into asthma management, supporting precision medicine.

Conclusions:

  • AI and ML are valuable instruments for improving accuracy in asthma diagnosis, classification, and risk assessment.
  • These technologies have the potential to personalize asthma treatment and prevent exacerbations.
  • AI will augment, not replace, clinicians, optimizing medical decisions and practices in asthma care.