Pulmonology

Development of an interpretable machine learning model-based online tool for risk identification of anxiety symptoms in Chinese older adults.

BACKGROUND: As the population aging process has accelerated, anxiety symptoms (AS) among older adults have become a critical concern. In addition to developing an online computational tool to identify high-risk persons in community settings, this study intends to construct and verify an interpretable machine learning (ML) model for identifying AS in older adults. METHODS: In accordance with the he...

Host-focused immunity, metabolism, and diagnostic innovation for precision control of tuberculosis globally.

Tuberculosis (TB), caused by Mycobacterium tuberculosis (MTB), remains one of the deadliest infectious diseases worldwide. Despite advances in treatment and diagnostics, challenges such as multidrug resistance, inadequate vaccines, diagnostic gaps and health inequities continue to impede global control efforts. This review explores emerging insights into host-pathogen interactions, with emphasis o...

Plasma proteomic profiles of lung volume-based phenotypes in Tobacco-Exposed Individuals Without Spirometric COPD.

BACKGROUND: Among individuals with a history of smoking but preserved spirometry (tobacco exposed with preserved spirometry, or TEPS), lung volume-bas...

Interpretable Machine Learning Uncovers the Dominance of Oxygen Partial Pressure and Crystallinity in Mo-Doped In2O3 Thin Film Growth.

Data-driven approaches have accelerated materials discovery, yet they often remain "black boxes" that prioritize performance over physical understandi...

Natural language processing of biomedical text to map and prioritize protein-disease associations in HFpEF.

The validation of promising clinical biomarkers, molecular mechanisms, and novel drug targets in cardiovascular disease (CVD) is hindered by a vast an...

In-Hospital Mortality Prediction of Patients Requiring Extracorporeal Membrane Oxygenation Using Composite Lactate Metrics and Weight of Evidence Modeling.

BACKGROUND: Mortality prognostication in adult patients requiring extracorporeal membrane oxygenation (ECMO) is not accurate or established. We hypoth...

An optimized machine learning model based on hematological indicators for the noninvasive identification of baicalin's therapeutic effects in pulmonary hypertension.

Pulmonary hypertension (PH) is a progressive cardiopulmonary disorder with high mortality, necessitating non-invasive methods for early detection and ...

Smart Garment for Continuous Respiration Monitoring in Canines.

There is a growing need for at-home respiration monitoring in canines, who are prone to respiratory issues due to breed-specific anatomy and active li...

Integrated CTC Enrichment and Dual-Responsive Nanoprobe Identification Enable Intelligent Liquid Biopsy-Based Cancer Diagnosis.

This work addresses the challenge of accurately identifying living circulating tumor cell (CTC) from contaminating leukocytes by developing a novel, f...

AI-Assisted Lung Sliding Detection in Point-of-Care Ultrasound by Marine Corps Corpsmen: A Multi-Reader Study.

BACKGROUND: Artificial intelligence (AI) has the potential to address training limitations and inter-operator variability that constrain the use of lu...

Performance validation of an artificial intelligence-assisted chest radiograph algorithm for incidental pulmonary nodule detection in Malaysian healthcare facilities: a multicentre cross-sectional study protocol.

INTRODUCTION: Incidental pulmonary nodules (IPNs) are commonly encountered on chest radiographs (CXRs) performed for routine clinical indications and ...

Clinical value of ultra-low-dose chest CT with deep learning image reconstruction in the detection and characterization of pulmonary nodules.

OBJECTIVE: To evaluate the clinical value of ultra-low-dose CT (ULDCT) with deep learning image reconstruction (DLIR) in the diagnosis of pulmonary no...

GSDME-mediated pyroptosis modulates the immunosuppressive microenvironment in lung adenocarcinoma.

Despite the increasing recognition of pyroptosis, particularly that involving GSDME, its precise impact on tumor prognosis and the immune microenviron...

Bayesian machine learning enables discovery of risk factors for hepatosplenic multimorbidity related to schistosomiasis.

One in 25 deaths worldwide is related to liver disease, and often with multiple hepatosplenic conditions. Yet, little is understood of the risk factor...

Integration of circulating tumor DNA data enhances lung cancer prediction in patients with COPD.

Patients with chronic obstructive pulmonary disease (COPD) are at increased risk of lung cancer, and the identification of circulating tumor DNA (ctDN...

Predicting pyrazinamide resistance in Mycobacterium tuberculosis using a graph convolutional network.

Prediction of high-flow nasal cannula failure in critically ill patients: a narrative review.

High-flow nasal cannula (HFNC) therapy is widely used for respiratory support in critically ill patients, offering benefits such as improved oxygenati...

18F-FDG PET/CT and receptor-positive circulating tumor cells-based machine learning model for predicting poorly differentiated lung adenocarcinoma.

INTRODUCTION: This study aimed to develop and validate a machine learning model that integrates radiomic features from 2-[18F]fluoro-2-deoxy-D-glucose...

Tuberculosis Drug Discovery in the Age of Artificial Intelligence.

There is an urgent need to develop additional treatments for tuberculosis (TB) to complement the small panel of approved drugs and to devise shorter t...

A Deep Learning Framework Integrating Tumor Microenvironmental Features Accurately Predicts Multiple Driver Gene Mutations in Lung Cancer Pathology Images.

UNLABELLED: Deep learning (DL) has the potential to enable the prediction of gene mutations directly from routine histopathology slides in lung cancer...