Pulmonology

Manganese Metabolism-Related Gene Signatures as Diagnostic Biomarkers for Tuberculosis: Immune Infiltration Profiling and Molecular Subtype Identification.

BACKGROUND: Host metabolic programs are increasingly recognized as key modulators of tuberculosis (TB) immunopathology, yet manganese metabolism-related transcriptional signatures with diagnostic and immunological relevance remain insufficiently characterized. We aimed to identify manganese metabolism-linked biomarkers for TB diagnosis and to delineate their immune and regulatory context. METHODS:...

Pulmonary nodule prediction in the multi-omics era: integrating radiomics, AI, liquid biopsy, and airway classifiers.

Low-dose CT (LDCT) lung cancer screening significantly reduces mortality but has dramatically increased the detection of pulmonary nodules. Most of these nodules are benign, leading to a high false-positive rate that triggers unnecessary invasive procedures and patient anxiety, underscoring the need for more precise noninvasive diagnostic tools. Critically, single-modality liquid biopsy biomarkers...

Internally validated machine learning models identify asthma and its phenotypes using multicenter real-world data.

Asthma exhibits significant clinical heterogeneity, necessitating precise phenotyping for personalized treatment. This study aims to develop and inter...

Applying prior knowledge of regulatory signaling to investigate macrophage cAMP dynamics during Mycobacterium tuberculosis infection.

Mycobacterium tuberculosis (Mtb), the causative agent of Tuberculosis, resides in host lung macrophages and has evolved unique processes to hijack hos...

Development of an expert-annotated chest X-ray dataset to support AI validation in tuberculosis diagnosis.

OBJECTIVES: To assess inter-rater agreement and diagnostic performance of six United States National Institute for Occupational Safety and Health-cert...

Performance evaluation of five major large language models in tuberculosis Q&A systems: A multidimensional assessment of readability, quality, and reliability.

BACKGROUND: Pulmonary tuberculosis (TB) is a chronic infectious disease that burdens patients and public health systems. Limited reach of traditional ...

A late fusion multi-task learning for respiratory waveform and rate estimation from photoplethysmography.

Continuous respiratory monitoring enables early detection of physiological deterioration, yet conventional capnography remains impractical for prolong...

Machine learning-based analysis of drug resistance mutations in Mycobacterium tuberculosis.

Tuberculosis is a deadly airborne disease caused by Mycobacterium tuberculosis. Drug-resistant tuberculosis presents significant challenges for treatm...

Study on the construction and verification of intraoperative pressure injury risk prediction model for children undergoing cardiac surgery.

BACKGROUND: This study applied nomogram to develop an intraoperative acquired pressure injury (IAPI) risk prediction model for pediatric cardiac surge...

Machine learning approach to analyzing complex care coordination patterns for medically complex children.

BACKGROUND: The number of children with medical complexity (CMC) in Japan has exceeded 20,000, doubling over the past 15 years, forming a significant ...

Decoding the role of phthalate plasticizers (DBP, DOP, and DEHP) in idiopathic pulmonary fibrosis: an integrated network toxicology and machine learning approach.

The molecular mechanism of idiopathic pulmonary fibrosis (IPF) caused by phthalate (PAE) is not well understood, presenting notable clinical and toxic...

Machine learning models predicting extubation success in mechanically ventilated patients: a systematic review and meta-analysis.

BACKGROUND: Optimal timing of extubation in mechanically ventilated patients remains a major challenge in intensive care. Machine learning (ML) models...

Deep Learning-Enabled Robust Regional Lung Function Assessment in Mechanically Ventilated AECOPD Patients Using EIT Parameters.

Reliable quantification of regional lung function via electrical impedance tomography (EIT) in mechanically ventilated AECOPD patients requires identi...

ASTHMA AT THE CROSSROADS: FROM ANTI-TNF-α SETBACKS TO NEXT-GENERATION BIOLOGICS TARGETING TYPE 1 AND TYPE 2 INFLAMMATION.

Severe asthma remains a major unmet clinical challenge due to its marked immunological heterogeneity and the limited efficacy of current therapies in ...

Development and validation of a disease-syndrome integrated assessment model for AECOPD severity: protocol for a nationwide multicentre cross-sectional study.

INTRODUCTION: Acute exacerbations of chronic obstructive pulmonary disease (AECOPD) accelerate disease progression and increase mortality. Accurate se...

Construction and validation of an interpretable machine learning model for predicting diabetes risk in COPD patients.

To construct and validate a machine learning (ML) model for predicting diabetes risk in COPD patients, enabling early and personalized intervention. U...

Current progress and future directions of intraoperative frozen section for spread through air spaces in lung cancer.

Spread through air spaces (STAS) is a recently recognized pattern of invasion in lung cancer that is strongly linked to postoperative recurrence and p...

Automated high-resolution computed tomography analysis outperforms visual assessment in predicting interstitial lung disease progression in systemic sclerosis.

OBJECTIVES: Progressive interstitial lung disease (ILD) is the leading cause of mortality in systemic sclerosis (SSc). Early recognition of progressio...

Fostering trust in digital respiratory medicine: the open access ERS CONNECT digital health technology repository.

Access to digital health tools is rapidly expanding, but adoption in respiratory care remains fragmented. The ERS CONNECT Repository provides a truste...

Digital Pathology-Enabled Artificial Intelligence for Fibrosis Assessment in Metabolic Dysfunction-Associated Steatohepatitis: Needs, Current Progress, and Barriers.

Metabolic dysfunction-associated steatotic liver disease (MASLD) is emerging as the most common chronic liver disorder worldwide. However, most of the...