Pulmonology

Asthma

Latest AI and machine learning research in asthma for healthcare professionals.

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An Experimentation Platform for On-Chip Integration of Analog Neural Networks: A Pathway to Trusted and Robust Analog/RF ICs.

We discuss the design of an experimentation platform intended for prototyping low-cost analog neural...

Time-Aware Tranformer-Based Prediction Model for AECOPD.

The rapid symptom change of Acute exacerbation of chronic obstructive pulmonary disease (AECOPD) mak...

Glucagon-like Peptide-1 Receptor Agonists in Asthma Exacerbations: An Application of High-Dimensional Iterative Causal Forest to Identify Subgroups.

BACKGROUND: Glucagon-like Peptide-1 Receptor Agonists (GLP1RA) may reduce asthma exacerbation (AE) r...

The impact of clinical history on the predictive performance of machine learning and deep learning models for renal complications of diabetes.

BACKGROUND AND OBJECTIVE: Diabetes is a chronic disease characterised by a high risk of developing d...

Artificial Intelligence Powered Audiomics: The Futuristic Biomarker in Pulmonary Medicine - A State-of-the-Art Review.

AI-driven "audiomics" leverages voice and respiratory sounds as non-invasive biomarkers to diagnose ...

Single-cell RNA sequencing reveals immunological link between house dust mite allergy and childhood asthma.

Allergic asthma in children is typically associated with house dust mites (HDM) as the key allergen....

Emerging Copper-to-Copper Bonding Techniques: Enabling High-Density Interconnects for Heterogeneous Integration.

As CMOS technology continues to downsize to the nanometer range, the exponential growth predicted by...

Predictive machine learning algorithm for COPD exacerbations using a digital inhaler with integrated sensors.

PURPOSE: By using data obtained with digital inhalers, machine learning models have the potential to...

Predicting prolonged hospitalization in asthma patients: model development and external validation.

PURPOSE: This study aims to develop and validate a machine learning (ML) model to predict prolonged ...

A Call for Integrated Approaches in Digital Technology Design for Aging and Disability.

The fields of aging and disability often proceed as 2 distinct lines of inquiry and action in terms ...

Artificial Intelligence-Generated Answers to Patients' Questions on Asthma: The Artificial Intelligence Responses on Asthma Study.

BACKGROUND: Asthma is a prevalent chronic respiratory disease requiring ongoing patient education an...

Predicting outcomes after hospitalisation for COPD exacerbation using machine learning.

BACKGROUND: Early readmission and death are critical adverse outcomes following hospitalisation due ...

Deep Learning for Predicting Acute Exacerbation and Mortality of Interstitial Lung Disease.

Some patients with interstitial lung disease (ILD) have a high mortality rate or experience acute e...

Clinical and Social Characterization of Patients Hospitalized for COPD Exacerbation Using Machine Learning Tools.

OBJECTIVE: This study aims to employ machine learning (ML) tools to cluster patients hospitalized fo...

Audio-based digital biomarkers in diagnosing and managing respiratory diseases: a systematic review and bibliometric analysis.

Advances in wearable sensors and artificial intelligence have greatly enhanced the potential of digi...

The Role of AI in Reshaping Medical Education: Opportunities and Challenges.

Artificial intelligence (AI) is redefining medical education, bringing new dimensions of personalize...

PNL: a software to build polygenic risk scores using a super learner approach based on PairNet, a Convolutional Neural Network.

SUMMARY: Polygenic risk scores (PRSs) hold promise for early disease diagnosis and personalized trea...

Identification of potential diagnostic markers and molecular mechanisms of asthma and ulcerative colitis based on bioinformatics and machine learning.

BACKGROUNDS: Asthma and ulcerative colitis (UC) are chronic inflammatory diseases linked through the...

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