Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Asthma-IV: Diagnostic and Management01:30

Asthma-IV: Diagnostic and Management

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:
Asthma-IV: Nursing Management01:30

Asthma-IV: Nursing Management

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...
Asthma: Pathogenesis and Management01:20

Asthma: Pathogenesis and Management

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.
Asthma-I: Introduction01:29

Asthma-I: Introduction

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...
Antiasthma Drugs: Mast Cell Stabilizers and Anti-IgE Drugs01:25

Antiasthma Drugs: Mast Cell Stabilizers and Anti-IgE Drugs

Asthma is a chronic respiratory condition for which new therapeutic avenues, including anti-inflammatory drugs like mast cell stabilizers and anti-IgE treatments, continue to be developed.
Mast cell stabilizers, such as cromolyn (also known as sodium cromoglycate) and nedocromil (Tilade), are effective drugs in asthma management. These stabilizers hinder histamine release by skillfully obstructing the activation of mast cells and other cellular entities. Notably, they navigate this task without...
Asthma I: Introduction01:28

Asthma I: Introduction

Asthma is a chronic inflammatory disorder of the airways characterized by variable airflow obstruction and heightened bronchial responsiveness to a wide range of triggers. The underlying inflammation leads to airway swelling, mucus hypersecretion, and smooth muscle constriction, all of which narrow the airway lumen and impede airflow. Clinically, asthma presents with recurrent episodes of wheezing, shortness of breath, chest tightness, and coughing, symptoms that typically vary in intensity and...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Autoimmune Disease Risk With GLP-1RA, DPP-4i, and SGLT2i Treatment in Patients With Diabetes.

ACR open rheumatology·2026
Same author

Type 2 Diabetes and the Lung - Cause and Consequence.

Current diabetes reports·2026
Same author

Respiratory Biologics Utilization, Prescription Predictors, and Outcomes in Patients With Asthma and Comorbid Overweight or Obesity.

The journal of allergy and clinical immunology. In practice·2026
Same author

Evaluating the integration of a COVID-19 symptom checker into an asthma-focused mHealth application.

Healthcare (Amsterdam, Netherlands)·2025
Same author

Dosing Reactions and Missed Doses Affect Peanut Oral Immunotherapy Outcomes.

The journal of allergy and clinical immunology. In practice·2025
Same author

Management of Patients With Comorbid Asthma and Obesity: A Large Language Model Evaluation of Clinical Documentation.

The journal of allergy and clinical immunology. In practice·2025

Related Experiment Video

Updated: Jun 30, 2026

Asthma Detection Research Based on Voice Signal Processing and Machine Learning
04:04

Asthma Detection Research Based on Voice Signal Processing and Machine Learning

Published on: July 22, 2025

Harnessing Machine Learning and Electronic Health Record Data to Improve Asthma Management.

Oluwatobi Olayiwola1, Dinah Foer2,3,4

  • 1Division of Allergy and Clinical Immunology, Brigham and Women's Hospital, Boston, Massachusetts, USA.

Current Allergy and Asthma Reports
|June 29, 2026
PubMed
Summary

Machine learning (ML) and large language models (LLMs) show promise for personalized asthma management using electronic health records. Rigorous validation and collaboration are key to realizing their potential in patient care.

Keywords:
Artificial intelligenceAsthma exacerbationsChatbotsDigital inhalersLarge language modelNatural language processing

Related Experiment Videos

Last Updated: Jun 30, 2026

Asthma Detection Research Based on Voice Signal Processing and Machine Learning
04:04

Asthma Detection Research Based on Voice Signal Processing and Machine Learning

Published on: July 22, 2025

Area of Science:

  • Artificial Intelligence in Medicine
  • Digital Health
  • Respiratory Medicine

Background:

  • Asthma management is evolving with technological advancements.
  • Electronic health records (EHRs) offer rich data for clinical insights.
  • Machine learning (ML) and large language models (LLMs) are emerging tools in healthcare.

Purpose of the Study:

  • To review the application of ML and LLMs in asthma management.
  • To identify clinically relevant applications, especially those using EHR data.
  • To explore challenges and future directions for these technologies in asthma care.

Main Methods:

  • Systematic review of ML and LLM applications in asthma.
  • Analysis of studies utilizing EHR data for asthma management.
  • Evaluation of current tools and their limitations.

Main Results:

  • ML in EHRs predicts medication response and exacerbation risk with moderate-to-high accuracy.
  • Digital inhalers improve adherence; chatbots aid patient education.
  • LLMs offer patient education tools but face accuracy and health literacy challenges.

Conclusions:

  • ML and LLMs present opportunities for data-driven, personalized asthma care.
  • External validation, transparency, and clinician oversight are crucial for implementation.
  • Multidisciplinary collaboration is essential for patient-centered integration of these technologies.