Asthma

From phenotypes to trajectories: Machine learning in asthma beyond labels.

Animal Models of Allergen Immunotherapy for Allergic Airway Inflammation.

Allergen immunotherapy (AIT) is currently the only disease-modifying therapy for allergic airway inflammation. However, its underlying mechanisms remain incompletely understood, which in turn impede the development of more effective and durable treatment strategies. Although animal models are indispensable for mechanistic dissection and therapeutic innovation, they are limited by significant trans...

Benchmarking Hybrid CNN-Transformer Versus Pure Transformer Architectures for Accelerated Hyperpolarized 129Xe MRI Reconstruction.

BACKGROUND: Hyperpolarized 129Xe MRI faces technical challenges including low signal-to-noise ratio and breath-hold constraints. Current literature fo...

Etiologic diagnosis of seasonal allergic rhinitis supported by artificial intelligence: the @IT-2020 project.

BACKGROUND: A precise etiological diagnosis of seasonal allergic rhinitis (SAR) is essential for a tailored prescription of its only curative treatmen...

Explainable machine learning for long-term cardiovascular disease risk prediction in Chinese middle-aged and older adults: a 9-year longitudinal cohort study with web-based risk calculator.

Cardiovascular disease represents the leading cause of mortality in China, accounting for over 40% of all deaths. Existing risk prediction models pred...

Identifying Undiagnosed COPD Using Machine Learning-Based Classification.

BACKGROUND: COPD is a leading cause of morbidity and mortality worldwide. However, 80% of individuals with COPD are undiagnosed, leading to accelerate...

Severe COVID-19 in the Republic of Korea: Epidemiology, Risk Factors, Therapeutics, and Prognostic Models From Nationwide Data.

Severe coronavirus disease 2019 (COVID-19) has posed ongoing clinical and public health challenges worldwide, with Korea providing a unique perspectiv...

Communication, compassion, and shared decision-making in allergy.

Shared decision-making (SDM) is a structured approach to clinical care that integrates the best available evidence, clinician expertise, and patient v...

Integrating bioinformatics, machine learning and molecular biology to elucidate the anti-allergic mechanisms of ginkgo biloba leaves.

Allergic diseases, encompassing allergic asthma, atopic dermatitis, food allergies, have emerged as substantial global public health challenges, with ...

Explainable Artificial Intelligence for Predicting Length of Stay and Treatment Response in Pediatric Asthma and Allergic Rhinitis: An Irregular Fuzzy Cellular Automata Approach Across Pre- and During-COVID-19 Periods.

OBJECTIVE: The COVID-19 pandemic significantly altered treatment strategies and healthcare utilization patterns in pediatric respiratory diseases. Giv...

[Care for uncontrolled asthma in Germany - with focus on Magdeburg and Mannheim regions].

Description of treatment and prescription patterns among asthma patients in the regions of Magdeburg (MD) and Mannheim (MA) compared nationwide.We ana...

Optimization and validation of air impingement cleaning parameters for removing nonfat dry milk powder from stainless steel surfaces by machine learning.

Air impingement cleaning can remove residues from food contact surfaces without introducing moisture, thereby controlling allergen cross-contact and p...

AI-Enhanced Conversational Agents for Personalized Asthma Support in People With Asthma: Factors for Engagement, Value, and Efficacy in a Cross-Sectional Survey Study.

BACKGROUND: Asthma-related deaths in the United Kingdom are the highest in Europe, and only 30% of patients access basic care. There is a need for alt...

CT image-based machine learning models for predicting blood eosinophil levels in acute exacerbation of chronic obstructive pulmonary disease.

Future Perspectives for Artificial Intelligence in Allergy: Advances in Diagnosis, Monitoring, and Personalized Care.

Artificial intelligence (AI) is significantly transforming the specialty of allergy by offering novel tools for diagnosis, risk prediction, disease mo...

GOLD 2026: Transforming COPD Management with Early Intervention, Multi-dimensional Assessment, and Personalized Care.

The 2026 report from the Global Initiative for Chronic Obstructive Lung Disease (GOLD) introduces substantial conceptual and practical updates to the ...

Wearable Sleep Measures May Improve Machine Learning Prediction of Home-Based Pulmonary Rehabilitation Engagement Among Patients With Chronic Obstructive Pulmonary Disease: A Proof-of-Concept Study.

OBJECTIVE: To evaluate whether incorporating baseline sleep measures from a wrist-worn activity monitor in machine learning (ML) models improved the p...

Artificial intelligence-associated delusions and large language models: risks, mechanisms of delusion co-creation, and safeguarding strategies.

Large language models (LLMs) are poised to become a ubiquitous feature of everyday life, mediating communication, decision making, and information cur...

Psychosis Risk and Generative Artificial Intelligence Use Frequency, Motivations, and Delusion-Like Experiences: Cross-Sectional Survey Study.

BACKGROUND: Growth of generative artificial intelligence (GenAI) has exploded in recent years. Many have noted its substantial potential to increase a...

Highlights from the Italian National Congress of Imaging in Pulmonology 2025: fostering implementation of advanced technologies for precision patient-centered care.

The Italian National Congress of Imaging in Pulmonology, held in Milan on November 21st, provided a unique educational platform exploring the evolving...