Pulmonology

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 subtype of phrenic motor facilitation (pMF), which also includes pharmacologically induced plasticity. Understanding the mechanisms of pLTF and pMF represents opportunities for therapeutic targets for spinal cord injury, amyotrophic lateral sclerosis and o...

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 and to assess repeatability of automated ADC quantification. METHODS: We proposed ADCSegNet, a deep learning model tailored to pulmonary ADC maps, trained and tested on ADC maps from centre 1 (303 MRI examinations) and externally evaluated on dataset...

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...

Hybrid supervised deep learning for lung adenocarcinoma diagnosis to optimize surgical strategies.

Intraoperative frozen section pathological diagnosis of lung adenocarcinoma serves as the gold standard for determining the extent of surgical resecti...

Development of machine learning and nomogram models to predict lung metastasis and prognosticate survival in breast cancer.

PURPOSE: Lung metastasis in breast cancer (BCLM) is a critical determinant of poor prognosis, occurring in approximately 30-50% of advanced cases and ...

Cauchy Lotus Optimization-based feature selection and ResNet 101 based XceptionNet architecture for radiation pneumonitis prediction in lung cancer patients.

Thoracic radiotherapy for lung cancer patients followed by radiation pneumonitis (RP) has significant clinical side effects. Risk-adaptive treatment p...

Artificial intelligence (AI)-assisted ultrasound in clinical trials: Endpoint automation, decentralized monitoring, and regulatory readiness.

Ultrasound is among the most widely used imaging modalities in clinical trials, and yet its dependence on operator skill and equipment settings has hi...

Combining cutting edge computational and experimental methods for targeting kras mutations in non-small cell lung cancer.

INTRODUCTION: Historically, KRAS mutations have been notoriously difficult to target despite their status as the most commonly mutated oncogene in the...

A Transformer-ResNet-Integrated Deep Learning Model for Digital Pathology-Based Grading and Risk Stratification of MASLD-Related Liver Fibrosis.

INTRODUCTION: Metabolic dysfunction-associated steatotic liver disease (MASLD) affects up to 30% of the global population and drives progression to fi...

A Roadmap to Transform Lung Cancer Outcomes: Priorities in Biology, Therapeutic Innovation, Early Detection, Prevention and Interception.

Advances in targeted therapies, immunotherapy, and early detection have revolutionized lung cancer treatment and extended survival. Nonetheless, lung ...

Effective elimination of respiratory misregistration-induced attenuation correction errors in PET/CT via deep learning trained on data-driven gated PET from strictly respiratory-phase-matched PET/CT cases.