Pulmonology

Inverse design and discovery of high entropy alloy catalysts for efficient oxygen evolution reaction.

High-entropy alloys (HEAs) consisting of earth-abundant elements can serve as replacement for expensive, industrial grade catalysts, such as iridium dioxide IrO2, for oxygen evolution reactions (OERs). However, navigating the exponential configuration space of possible HEAs and unknown inverse structure-property relationship has hindered the development of HEAs for efficient electrocatalytic appli...

Machine learning identification of neuroimaging signatures in young and middle-aged male patients with obstructive sleep apnea: a multimodal MRI study.

OBJECTIVES: This study aimed to develop and validate an integrated neuroimaging-based model for identifying severe obstructive sleep apnea (OSA) with severe oxygen desaturation (ODI ≥ 30 events/hour) in young and middle-aged male. A key goal was to characterize the neuroimaging signatures associated with the hypoxic burden of OSA. METHODS: Data from 111 patients were utilized. The initial feature ...

Single-cell and multi-omics integration delineates the landscape of gene-wise intratumor heterogeneity and identifies prognostic biomarkers for immunotherapy in non-small cell lung cancer.

BACKGROUND: Gene-wise intratumor heterogeneity (ITH), defined as spatial variability in the expression of individual genes across tumor regions, remai...

Multidimensional immunoinflammatory profiles associated with rheumatoid arthritis-associated interstitial lung disease: a cross-sectional exploratory study.

OBJECTIVE: To investigate the associations of non-invasive peripheral blood inflammatory indices, cytokines, and lymphocyte subsets with the risk of r...

Phenotyping of pulmonary arterial hypertension associated with congenital heart disease using latent class analysis: insights from a national prospective registry.

BACKGROUND: Pulmonary arterial hypertension associated with congenital heart disease (PAH-CHD) is characterized by substantial prognostic and therapeu...

A machine learning model for predicting pneumothorax risk after computed tomography-guided percutaneous transthoracic needle biopsy: A two-hospital retrospective study.

Pneumothorax is a common complication after computed tomography-guided percutaneous transthoracic needle biopsy (PTNB), but individualized prediction ...

Training set augmentation and biology-aware harmonization improve radiomic models for lung cancer prediction in indeterminate nodules.

CT radiomics-based machine learning has potential to predict lung cancer in pulmonary nodules (PNs) earlier than standard-of-care methods. Low maligna...

Association between long-term PM2.5 exposure and risk of urinary tract infection in children: a nationwide longitudinal cohort study.

BACKGROUND: Urinary tract infection (UTI) is among the most common bacterial infections in children and can lead to both acute and chronic complicatio...

Decoding chromatin regulator-LAIR1+ M2 like macrophage patterns in atherosclerosis and clinical outcomes of Lung adenocarcinoma patients: evidence from artificial intelligence-driven multi omics and in vitro validation.

Atherosclerosis (AS) is a common complication of lung adenocarcinoma (LUAD), but its underlying mechanisms in LUAD remain unclear. This study aimed to...

Deep learning-based CT slice synthesis improves radiomic feature reproducibility and discriminative performance in lung nodule assessment.

OBJECTIVES: To investigate the effect of CT slice thickness on radiomic features (RFs) in terms of reproducibility and discriminative power, and to as...

Preoperative and intraoperative localization of small pulmonary nodules for thoracoscopic surgery: a contemporary narrative review.

For thoracoscopic resection to be successful, accurate preoperative and intraoperative localization is necessary due to the growing detection of small...

Artificial Intelligence in Pediatric Imaging: A Primer for Pediatric Clinicians.

Artificial intelligence (AI) is reshaping healthcare, and radiology is at the forefront for adoption. Increasing demand for imaging, complex protocols...

Interpretable Machine Learning for Early Risk Stratification of Carbapenem Resistance Among ICU Patients with Sterile-Site Pseudomonas aeruginosa Isolates: Development and Internal Validation Using MIMIC-IV.

OBJECTIVES: We developed and internally validated an interpretable machine learning model to stratify carbapenem-resistance probability among ICU pati...

AutoRV: Automated Assessment of Right Ventricular Structure and Function Using Transesophageal Echocardiography in Mechanically Ventilated Patients.

OBJECTIVE: Right ventricle (RV) dysfunction has therapeutic implications for the management of mechanically ventilated patients in intensive care unit...

Deep learning-based myocardial infarction detection using echocardiography.

Myocardial infarction (MI) is a life-threatening condition caused by reduced oxygen supply to the heart muscle due to blockage of the coronary arterie...

Pancreatic organoids and organoid-on-a-chip platforms: from disease modeling to precision therapy.

BACKGROUND: Pancreatic diseases, including diabetes, pancreatic ductal adenocarcinoma, pancreatitis, and cystic fibrosis, impose a substantial clinica...

Machine learning-driven QSAR modeling combined with single cell transcriptomics identifies novel drug targets for lung cancer.

BACKGROUND: Non-small cell lung cancer (NSCLC) is a leading cause of cancer-related mortality, largely due to frequent metastasis to the brain and bon...

Pathway-level epigenetic modeling illuminates the methylation architecture to asthma risk across tissues.

BACKGROUND: Asthma is a clinically heterogeneous airway disorder characterized by complex interactions between environmental exposures, immune activat...

Machine learning model for early prediction of acute respiratory failure in acute pancreatitis: Multicenter validation.

Acute respiratory failure (ARF) is a common organ failure in acute pancreatitis (AP) with high mortality. This study used machine learning to predict ...

Differentiating sub-centimeter lung metastases in colorectal cancer by deep learning: a multicenter retrospective study.

BACKGROUND: Early diagnosis of sub-centimeter lung metastases is critical for timely decision-making and improved prognosis in patients with colorecta...