Pulmonology

Developing and validating an electronic health record-embedded AI model for managing multimorbid hospitalisation risk in patients with chronic RESpiratory disease (AiRES): a study protocol.

BACKGROUND: Chronic respiratory diseases (CRDs), such as asthma and chronic obstructive pulmonary disease (COPD), are heterogeneous conditions with a high multimorbidity burden. However, existing risk assessment instruments prioritise physiological measures while overlooking systemic comorbidities. We aim to develop and validate an electronic health record (EHR)-embedded artificial intelligence (A...

CFTR modulator therapy reshapes airway inflammation in cystic fibrosis: Insights from proteomics and machine learning.

BACKGROUND: CFTR modulators, including Elexacaftor/Tezacaftor/Ivacaftor (ETI), have markedly improved clinical outcomes for people with cystic fibrosis (pwCF), but the molecular impact on airway inflammation remains incompletely understood. This study aimed to characterise longitudinal changes in airway inflammation and sputum proteomes following ETI treatment. METHODS: Sputum from pwCF (n = 30) w...

A lifecycle governance and learning health system framework for trustworthy, generalizable, and sustainable human-ai partnership in clinical practice: Lessons from the asthma-guidance and prediction system (A-GPS).

The integration of artificial intelligence (AI) into clinical decision support (CDS) holds promise for proactive, personalized, and precision care. Ho...

Development and validation of a deep learning model for liver shear stiffness regression using abdominal multiparametric MRI across multiple sites and vendors.

OBJECTIVE: Liver stiffness measurement is important for assessing chronic liver disease (CLD). MR elastography (MRE) requires specialized hardware and...

Deep-Motion-Net: GNN-based volumetric liver shape reconstruction from single-view 2D projections.

PURPOSE: Internal anatomical motion challenges precise radiation delivery during external beam radiotherapy. Estimating and compensating for anatomica...

Harnessing hybrid stacking ensemble learning for accurate pulmonary embolism diagnosis using tabular clinical data.

Pulmonary Embolism (PE) is a serious condition that can be life-threatening if not diagnosed promptly as timely clinical decisions are critical. This ...

Usefulness of lung sound data collection using Skeeper SM-300® device: A pilot study.

BACKGROUND: Digital stethoscope has been introduced to clinical practice and are developing in many aspects. Overwhelming pandemic requires non-contac...

The challenge of data scarcity and imbalanced classes in radiomics performance.

BACKGROUND AND OBJECTIVES: Radiomics-based machine learning models are increasingly used for clinical decision-making, yet their reliability is often ...

Deep residual network fusing CT images and clinical variables to predict lung adenocarcinoma aggressiveness.

BACKGROUND: Lung adenocarcinoma presenting as ground-glass nodules (GGNs) comprises three invasive subtypes (adenocarcinoma in situ [AIS], minimally i...

Machine learning-based study of breath sounds in children with asthma in remission and cough variant asthma.

BACKGROUND: Traditional auscultation, heavily dependent on the subjective judgment of physicians, can lead to variability in diagnoses. This study aim...

Interpretable machine learning for predicting in-hospital mortality in COPD ICU patients: a rigorous validation across time and geography.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) is a common reason for admission to the intensive care unit (ICU), where accurate risk strati...

Deep learning-based 3D leukocyte differentiation using label-free higher harmonic generation microscopy.

BACKGROUND: Both in clinical practice and translational research, cell differentiation of leukocytes provides important diagnostic information and ins...

Blood Pressure Assessment Across the Lifespan: Improving Clinical Research and Clinical Practice: A National Heart, Lung, and Blood Institute Workshop Report.

Hypertension is a modifiable risk factor for cardiovascular disease (CVD) and its prevalence is high in the United States and worldwide. Adequate char...

ARDSMLpred: A machine learning model for predicting SCAP-associated ARDS based on MIMIC-IV database.

BACKGROUND: Early identification of acute respiratory distress syndrome (ARDS) in severe community-acquired pneumonia (SCAP) are crucial for reducing ...

Thrombospondin-2 is a performant biomarker of at-risk MASH and advanced MASH fibrosis in a large multicentre European cohort.

BACKGROUND: Non-invasive biomarkers with biological rationale are needed for identifying patients with progressive metabolic dysfunction-associated st...

Defect-Induced Dynamic Reconstruction Boosts Oxygen Evolution Activity of Perovskite Oxides.

The intermittent nature of renewable energy calls for efficient storage, and electrochemical water splitting provides a route to convert electricity i...

Machine Learning for COPD Case Finding: Looking for the Haystack.

Integrative Bioinformatics, Experimental Validation, and Interpretable Machine Learning Reveal Oxyresveratrol-Mediated Protection Against Cadmium-Induced Lung Adenocarcinoma-Related Transcriptional Dysregulation.

Cadmium (Cd) is a toxic heavy metal strongly implicated in lung adenocarcinoma (LUAD) through mechanisms involving oxidative stress, epigenetic dysreg...

Wheeze detection in real-world pediatric care: AI applied to smartphone lung auscultation.

UNLABELLED: Smartphone-based lung auscultation, combined with artificial intelligence (AI), may offer a promising alternative for pediatric respirator...

Scalable Identification of Clinically Relevant Chronic Obstructive Pulmonary Disease Documents in Large-Scale Electronic Health Record Datasets With a Lightweight Natural Language Processing Model: Retrospective Cohort Study.

BACKGROUND: The widespread adoption of electronic health records has resulted in the generation of large volumes of clinical notes. Learning algorithm...