Pulmonology

MTMedFormer: multi-task vision transformer for medical imaging with federated learning.

Deep learning has revolutionized medical imaging, improving tasks like image segmentation, detection, and classification, often surpassing human accuracy. However, the training of effective diagnostic models is hindered by two major challenges: the need for large datasets for each task and privacy laws restricting the sharing of medical data. Multi-task learning (MTL) addresses the first challenge...

Deep Learning-Enhanced Hand-Driven Spatial Encoding Microfluidics for Multiplexed Molecular Testing at Home.

The frequent global outbreaks of viral infectious diseases have significantly heightened the urgent demand for molecular testing at home. However, the labor-intensive sample preparation and nucleic acid amplification steps, along with the complexity and bulkiness of detection equipment, have limited the large-scale application of molecular testing at home. Here, we propose artificial intelligence-...

Machine learning models using non-invasive tests & B-mode ultrasound to predict liver-related outcomes in metabolic dysfunction-associated steatotic liver disease.

Advanced metabolic-dysfunction-associated steatotic liver disease (MASLD) fibrosis (F3-4) predicts liver-related outcomes. Serum and elastography-base...

Machine learning assists regulated cell death crucial biomarker selection in adenocarcinoma of the lung: biological data testing and cell assay determination.

BACKGROUND: Lung cancer is a highly aggressive and lethal cancer requiring prognostic and predictive biomarkers for improving patient outcomes. Here, ...

Predictive models of influenza A virus lethal disease yield insights from ferret respiratory tract and brain tissues.

Collection of systemic tissues from influenza A virus (IAV)-infected ferrets at a fixed timepoint post-inoculation represents a frequent component of ...

Cellular senescence in renal ischemia-reperfusion injury.

Acute kidney injury (AKI) affects more than 20% of hospitalized patients and is a significant contributor to morbidity and mortality, primarily due to...

Shape matters: inferring the motility of confluent cells from static images.

Cell motility in dense cell collectives is pivotal in various diseases like cancer metastasis and asthma. A central aspect in these phenomena is the h...

Evaluation of AI-based detection of incidental pulmonary emboli in cardiac CT angiography scans.

Incidental pulmonary embolism (PE) is detected in 1% of cardiac CT angiography (CCTA) scans, despite the targeted aortic opacification and limited fie...

Unlocking potent anti-tuberculosis natural products through structure-activity relationship analysis.

Tuberculosis (TB) remains a world health problem due to the high number of affected individuals, high mortality rates, prolonged treatment durations, ...

Performance of a deep-learning-based lung nodule detection system using 0.25-mm thick ultra-high-resolution CT images.

PURPOSE: Artificial intelligence (AI) algorithms for lung nodule detection assist radiologists. As their performance using ultra-high-resolution CT (U...

Identifying and characterising asthma subgroups at high risk of severe exacerbations using machine learning and longitudinal real-world data.

OBJECTIVES: To identify and characterise distinct subgroups of patients with asthma with severe acute exacerbations (AEs) by using a multistep cluster...

Exploring tuberculosis patients' preferences for AI-assisted remote health management services in China: a protocol for a discrete choice experiment.

INTRODUCTION: Effective health management is critical for patients with tuberculosis (TB), especially given the need for long-term treatment adherence...

An enhanced fusion of transfer learning models with optimization based clinical diagnosis of lung and colon cancer using biomedical imaging.

Lung and colon cancers (LCC) are among the foremost reasons for human death and disease. Early analysis of this disorder contains various tests, namel...

Imaging and pulmonary function techniques in ARDS diagnosis and management: current insights and challenges.

Acute Respiratory Distress Syndrome (ARDS) is a life-threatening condition characterized by acute onset of respiratory failure, which presents signifi...

Identification of inflammation-related biomarkers and therapeutic targets for neurogenic bladder fibrosis via multi-omics analysis.

Inflammatory responses play a crucial role in the progression of pediatric neurogenic bladder (NB)-associated fibrosis; however, their specific contri...

Multimodal Optical Imaging Combined with Radiomic Analysis for Fibrotic Cardiac Tissue Investigation.

Understanding the process of fibrotic scarring of the myocardium is critical for the diagnosis and risk stratification of life-threatening cardiac dys...

Assessing chronic obstructive pulmonary disease risk based on exhalation and cough sounds.

BACKGROUND AND OBJECTIVE: Chronic obstructive pulmonary disease (COPD), a progressively worsening respiratory condition, severely impacts patient qual...

Advancements in Tuberculosis Diagnostics: An Update.

Tuberculosis (TB) is one of the major life-threatening diseases caused by a single pathogen which has become a social menace owing to its high resista...

Developing a Panel of Shared Susceptibility Genes as Diagnostic Biomarkers for chronic obstructive pulmonary disease and Heart Failure.

AIM: Chronic obstructive pulmonary disease (COPD) and heart failure (HF) are closely intertwined comorbidities that present significant clinical chall...

Disease Classification of Pulmonary Xenon Ventilation MRI Using Artificial Intelligence.

RATIONALE AND OBJECTIVES: Hyperpolarized Xenon magnetic resonance imaging (MRI) measures the extent of lung ventilation by ventilation defect percent ...