Pulmonology

Turmeric extracellular vesicles-derived "all-in-one" nanoagent enables full-cycle synergistic immunomodulation of lung cancer.

Lung cancer's metastatic propensity and recurrence prevalence necessitate innovative immunotherapy strategies beyond conventional single-mode regulation. We engineered low-capacity turmeric-derived extracellular vesicles (TEVs) that integrated with zeolitic imidazolate framework-8 (ZIF-8) to construct an "all-in-one" nanoagent, addressing both high drug loading nanocarriers production and immunolo...

Physics-aware imaging AI for quantitative MASLD biomarker mapping: a systematic review of deep learning and radiomics across ultrasound, CT, and MRI.

OBJECTIVE: This systematic review critically appraises the current landscape of physics-aware artificial intelligence (AI) in medical imaging for quantitative biomarker mapping in Metabolic dysfunction-associated steatotic liver disease (MASLD) and its progressive form, MASH. It focuses on deep learning and radiomics applications across ultrasound, CT, and MRI. METHODS: A PRISMA 2020-guided system...

Prospective Respiratory Motion Correction Using Machine Learning and Pilot Tone (PROMPT) in Cardiac MRI.

PURPOSE: To implement and evaluate the feasibility of a Pilot Tone (PT)-based prospective gating and tracking technique, which uses a long short-term ...

Application of a natural language processing algorithm to early asthma ascertainment for adults in the era of electronic health records.

BACKGROUND: The natural language processing (NLP) algorithm for predetermined asthma criteria (NLP-PAC) was successfully developed and validated for a...

Advances in antituberculosis drug-induced liver injury: Molecular mechanisms, genetic insights, and emerging animal-free prediction models.

Approximately 10 million tuberculosis patients worldwide require drug therapies annually. However, prolonged use of tuberculocidal drugs in combinatio...

Manuscript title: Impact of vessel suppression AI on reading efficiency and nodule detection in CT chest.

BACKGROUND: Vessel suppression (VS) software enhances pulmonary nodule conspicuity by attenuating vascular and fissural structures, but real-world imp...

Deep learning for non-invasive detection of steatosis and fibrosis in MASLD: a multicenter study with a new fibroscan-labelled ultrasound dataset.

PURPOSE: This study aimed to develop and validate deep learning models for non-invasive assessment of hepatic steatosis and fibrosis using conventiona...

Occupational Exposure to Welding Fumes Associated With Pulmonary Surfactant Lipid Compositional Changes, Inflammatory Activity, and Pulmonary Functioning.

OBJECTIVE: This study aimed to investigate alterations in the respiratory tract lining fluid phospholipids and their association with pulmonary functi...

Artificial intelligence‑based quantitative analysis of hepatic fibrosis in carbon tetrachloride-induced mouse model of metabolic dysfunction-associated steatohepatitis.

UNLABELLED: Liver fibrosis, a major histopathological indicator of chronic liver injury, is also a key feature of metabolic dysfunction-associated ste...

Development and validation of a machine learning model to predict 30-day mortality in ischemic stroke patients with consciousness impairment: Insights from MIMIC-IV database and multicenter ICU data in China.

BACKGROUND: Patients with ischemic stroke complicated by consciousness disorders remain associated with high mortality risks. This study aims to devel...

Regulatory mechanism of the oprM gene in colistin resistance of acinetobacter baumannii.

BACKGROUND: Colistin resistance in Acinetobacter baumannii (AB) is a serious clinical concern. This study aimed to identify resistance-related genes a...

Extreme cardiac MRI analysis under respiratory motion: Results of the CMRxMotion challenge.

Deep learning models have achieved state-of-the-art performance in automated Cardiac Magnetic Resonance (CMR) analysis. However, the efficacy of these...

Methodology for the Development of the Allergic Rhinitis and Its Impact on Asthma (ARIA)-EAACI 2024-2025 Guidelines: From Evidence-to-Decision Frameworks to Digitalised Shared Decision-Making Algorithms.

The Allergic Rhinitis and its Impact on Asthma (ARIA) guidelines produced their first edition in 1999, with subsequent revisions in 2008, 2010, 2016 a...

Nationwide longitudinal evaluation of a machine learning approach for enhanced interpretation of Xpert MTB/RIF ultra rifampicin-resistance results in low bacterial load tuberculosis specimens.

BACKGROUND: The World Health Organization (WHO) has identified tuberculosis (TB) as the leading cause of death from a single infectious agent. False-p...

Deep Learning Reconstruction for 129Xe Diffusion-Weighted MRI Enables Use of Natural Abundant Xenon and Improved Image Acceleration.

PURPOSE: (i) To assess whether 129Xe apparent diffusion coefficient (ADC) and diffusive length scale (LmD) metrics are quantitatively preserved with d...

Building a Quantitative Telemedicine Platform for Myasthenia Gravis: Augmenting the Physical Examination.

Myasthenia gravis (MG), a fluctuating autoimmune neuromuscular disease, presents unique challenges for remote assessment due to its reliance on detail...

Vit-Ensemble: Probabilistic voting based ensemble of Vision Transformers for tuberculosis detection using radiographs.

Tuberculosis (TB) detection from chest X-ray (CXR) images remains a critical challenge in global healthcare. This study introduces Vit-Ensemble, a nov...

Direction-Aware convolution for airway tubular feature enhancement network.

Manual annotation of airway regions in computed tomography images is a time-consuming and expertise-dependent task. Automatic airway segmentation is t...

Integrated multi-omics analyses identified the H3K18la-based spatiotemporal characteristics and risk-stratified treatment strategy in lung adenocarcinoma.

Lung adenocarcinoma (LUAD) is the most common histological type of lung cancer, characterized by high mortality, recurrence, and metastasis. Despite a...

Learning curve for fenestrated-branched endovascular aortic repair using machine learning: A prospective national multicenter registry study.

OBJECTIVE: Fenestrated-branched endovascular aortic repair (F-BEVAR) is a complex procedure that requires significant experience and advanced technica...