Asthma

PRACTALL 2025: Artificial intelligence-application of allergy and immunology to patient care.

Artificial intelligence (AI), first defined in 1955 by John McCarthy, has transformed daily life across industries through applications such as chatbots, autonomous vehicles, and navigation systems. The 2022 release of ChatGPT marked a pivotal moment, highlighting AI's rapidly expanding potential. The health care industry is increasingly embracing AI-enabled tools across oncology, pathology, and r...

Characterization and Validation of EHR Computable Phenotypes for Long COVID Using Patient-Reported Symptoms: Insights from the Nationwide RECOVER Program.

OBJECTIVE: Long COVID (LC) remains poorly understood, and there is a critical need for advanced computational tools to better identify and characterize patients. In this study, we use summarized symptom reports by RECOVER-Adult cohort participants linked to EHR data to characterize patients and train a computable phenotype algorithm of LC. MATERIALS AND METHODS: The study included adult participan...

Data-efficient machine learning approach for predicting asthma attack risk.

Asthma caused around 436,000 deaths globally in 2021. Predicting asthma attacks can save lives, reduce costs, and strengthen healthcare systems. Howev...

Internally validated machine learning models identify asthma and its phenotypes using multicenter real-world data.

Asthma exhibits significant clinical heterogeneity, necessitating precise phenotyping for personalized treatment. This study aims to develop and inter...

ASTHMA AT THE CROSSROADS: FROM ANTI-TNF-α SETBACKS TO NEXT-GENERATION BIOLOGICS TARGETING TYPE 1 AND TYPE 2 INFLAMMATION.

Severe asthma remains a major unmet clinical challenge due to its marked immunological heterogeneity and the limited efficacy of current therapies in ...

Preferential nitrogen retention characterizes current eutrophication in United States lakes.

The relative retention of nitrogen (N) and phosphorus (P) in lakes and their roles in nutrient cycling remain debated. Although the United States has ...

Federated deep learning for distributed intrusion detection and privacy preservation in power networks.

The deepening cyber-physical integration of smart grids has expanded the attack surface of power networks, while centralised intrusion detection schem...

Utility of E-Nose in Paediatric Respiratory Diseases Using Machine Learning Approach: A Pilot Study.

To assess the feasibility of an electronic nose (e-nose) for volatile organic compounds (VOCs) to classify respiratory diseases and establish a protoc...

Development and multicenter validation of machine learning models for 28-day mortality in critically ill patients with acute exacerbation of chronic obstructive pulmonary disease.

BACKGROUND: Acute exacerbation of chronic obstructive pulmonary disease (AECOPD) is a common critical illness in the intensive care unit (ICU) and is ...

DFT and machine learning investigation of Au/Pt-decorated SnS₂ monolayers for asthma and COPD diagnosis.

Asthma and Chronic Obstructive Pulmonary Disease (COPD) are among the most prevalent chronic respiratory diseases worldwide, affecting hundreds of mil...

Development and external validation of a dual-stage predictive model for self-reported physician-diagnosed chronic lung disease, asthma, and lung cancer in Chinese adults.

Chronic respiratory diseases represent a leading cause of global mortality, yet robust prediction tools integrating onset risk and long-term prognosis...

Identifying predictor factors for asthma using machine learning: evidence from the English Longitudinal Study of Ageing.

BACKGROUND: Asthma is a common chronic inflammatory airway disease. Accumulating evidence highlights the roles of demographic, lifestyle, and comorbid...

Machine learning-based MPO and Lp-PLA2 profiling reveals asthma-predominant inflammatory signature in asthma-COPD overlap.

BACKGROUND: Asthma-COPD overlap (ACO) remains poorly characterized at the molecular level, leading to diagnostic uncertainty and suboptimal treatment....

Informed Consent Disclosures and Minimum Requirements in AI Clinical Trials: Cross-Sectional Analysis.

BACKGROUND: The integration of artificial intelligence (AI) into clinical research challenges traditional informed consent (IC) frameworks due to the ...

Advancements in wearable technology for heart failure patients.

PURPOSE OF REVIEW: While pharmacologic and device therapies have improved heart failure care in recent decades, age-adjusted rehospitalization rates r...

Diagnostic Model Construction of Mitochondrial-Mitophagy Related Genes and Their Regulatory Network and Potential Drug Discovery in Childhood Allergic Asthma.

Childhood allergic asthma (CAA) is a chronic airway inflammatory disorder driven by allergens, and its underlying molecular mechanisms as well as prec...

Calceolarioside B alleviates airway barrier dysfunction and inflammation via targeting P2Y6R in OVA-triggered asthma.

Asthma is a chronic inflammatory airway disease characterized by barrier dysfunction and excessive inflammatory response. In this study, we identified...

Ambient AI in primary care: an exploratory mixed methods survey of UK general practitioners.

OBJECTIVE: To examine UK general practitioners' (GPs) adoption of ambient artificial intelligence (AI) scribes and to assess user-reported error rates...

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

PURPOSE OF REVIEW: The review examines the application of machine learning (ML) and large language models (LLMs) to asthma management. We sought to id...

Augmenting Pediatric Care With Artificial Intelligence: Opportunities and Responsibilities for Nurse Practitioners.

BACKGROUND: Artificial intelligence (AI) is emerging as a critical tool for nurse practitioners delivering pediatric and adolescent and young adult (A...