Pulmonology

Artificial intelligence construction: a review of the bridge between CT imaging features of lung ground-glass nodules adenocarcinoma and carcinogenic driver genes.

Lung ground-glass nodules (GGNs) represent a critical early imaging manifestation of lung adenocarcinoma, and exploring the relationship between their CT imaging features and oncogenic driver genes holds significant promise for precision diagnosis and personalized treatment. In recent years, artificial intelligence (AI) technologies, particularly deep learning and machine learning methods, have de...

FOSL2 regulates endothelial cell state and chromatin accessibility in systemic sclerosis pulmonary vascular remodeling.

Systemic sclerosis (SSc) is characterized by fibrosis and vasculopathy affecting the skin and internal organs, leading to multiorgan dysfunction. Injury of microvascular endothelial cells (ECs) in SSc impairs blood flow and causes tissue ischemia, leading to vascular complications such as Raynaud's, digital ulcers, and pulmonary hypertension (PH). PH in SSc presents as group 1 pulmonary arterial h...

Using a large language model artificial intelligence agent to improve the efficiency of clinical quality measure evidence evaluation: a case study.

OBJECTIVES: To evaluate the feasibility and performance of a large language model (LLM)-based artificial intelligence (AI) agent, implemented within a...

A new era of precision diagnosis and treatment for lung cancer: artificial intelligence-driven multimodal data integration and clinical applications.

Certain characteristics, such as high heterogeneity, a complex tumor microenvironment, metastatic potential, and drug resistance, render Lung cancer (...

DeepFAN, a transformer-based model for human-artificial intelligence collaborative assessment of incidental pulmonary nodules in CT scans: a multireader, multicase trial.

The widespread adoption of computed tomography has increased the detection of lung nodules. However, deep learning methods for classification of benig...

LSTM-GRU hybrid model for multi-layer microclimate prediction in solar greenhouse.

Precise microclimate control across vertical canopy layers is critical for optimizing crop production in horticulture solar greenhouses, yet existing ...

Key factors of the deranged antiviral response in elderly patients with COVID-19: a machine-learning analysis.

Age is a well-known risk factor to develop severe viral respiratory infections, including severe COVID-19. This study aimed to identify the biological...

Multiclass lung cancer detection using a hybrid capsule inspired deep neural network.

Convolutional Neural Networks are widely used in lung cancer detection for more than a decade. However, it suffers from preserving spatial relationshi...

Physiological predictors of respiratory motor plasticity: A machine-learning reappraisal of phrenic motor facilitation.

Acute intermittent hypoxia (AIH)-induced phrenic long-term facilitation (pLTF) is a well-established form of respiratory motor plasticity and a subtyp...

Deep learning-based segmentation and quantification of pulmonary masses on apparent diffusion coefficient maps: a multicentre reproducibility study.

OBJECTIVES: To develop and validate a deep learning model for automatic segmentation of pulmonary masses on apparent diffusion coefficient (ADC) maps ...

Decoding viral evolution through integrative bioinformatics: From genomes to global health.

Bioinformatics has transformed modern virology by linking genomic variation to epidemiology, protein structure, and public health action. This review ...

Divergent macrophage-regulated T cell states determine response to Bacillus Calmette-Guérin vaccine in high-risk bladder cancer.

BACKGROUNDPrimary therapy for high-risk bladder cancer (BCa) is repeated instillations of the tuberculosis vaccine Bacillus Calmette-Guérin (BCG). Alt...

Identification of potential MenT3 inhibitors for Mycobacterium tuberculosis using the generative artificial intelligence and SilicoXplore platform.

TCMNet: dynamic tanh enhanced 3D transformer with cascaded multiplicative fusion for pulmonary nodule detection.

Early detection of pulmonary nodules plays a critical role in improving the survival rate of patients with lung cancer. However, existing detection me...

Cohort vs case-control design for transformer-based prediction of asthma exacerbations in mild asthma.

Acute asthma exacerbation (AAE) is among the most serious outcomes of asthma, and accurate prediction of its risk remains a key challenge. Existing el...

Whole genome sequencing precision medicine strategy to shorten treatment for rifampicin-resistant tuberculosis (SMARTT): a pragmatic, randomised, single-blind phase 4 trial.

BACKGROUND: All patients with rifampicin-resistant tuberculosis should receive a short course of effective treatment. We aimed to evaluate the effecti...

Artificial Intelligence in Systemic Sclerosis: Clinical applications, challenges, and future directions.

Systemic sclerosis (SSc) is a rare autoimmune disease defined by immune dysregulation, vasculopathy, and progressive fibrosis of the skin and internal...

Interpretable Wavelet-CNN for Accurate Serum Raman Lung Cancer Diagnosis under Leakage-Safe, Patient-Level Splits.

Clinical cancer diagnostics require ML that maintains accuracy under biological variability with interpretable feature attribution─a particular challe...

Clinical utility of BOLD-MRI in accurate diagnosis and prognostic evaluation of diabetic nephropathy: a prospective renal biopsy-based cohort study.

OBJECTIVES: To validate blood oxygen level-dependent MRI (BOLD-MRI) for non-invasive discrimination of diabetic nephropathy (DN) vs non-diabetic renal...

Continuous Mobile Audio Monitoring for Sleep Apnea Detection.

Audio-based sleep apnea detection methods hold great potential to improve access to diagnosis, by providing unattended sleep apnea screening at home v...