Pulmonology

Leveraging Artificial Intelligence to Transform Thoracic Radiology for Lung Nodules and Lung Cancer: Applications, Challenges, and Future Directions.

This review traces the historical path of artificial intelligence (AI) methods that have been applied to medical image interpretation. Early AI approaches, which were based on clinical expertise and domain-specific medical knowledge, established the basis for data-driven methods, initiating the radiomics era and leading to the widespread use of deep learning in medical imaging. More recently, tran...

Quantitative CT and Artificial Intelligence in Chronic Lung Disease.

Computed tomography (CT) is routinely used in diagnosing and managing patients with chronic lung diseases such as chronic obstructive pulmonary disease (COPD) and fibrosing interstitial lung disease (ILD). Visual assessment of disease morphology/phenotype and extent correlates with lung function and patient prognosis, but it is limited by reader subjectivity and interobserver variability. Quantita...

Retrieval Augmented Generation (RAG) for Evaluating Regulatory Compliance of Drug Information and Clinical Trial Protocols.

The purpose was to evaluate retrieval-augmented generative (RAG) artificial intelligence (AI) methods for assessing the regulatory compliance of drug ...

A Self-Supervised Foundation Model Based on Three-Dimensional Chest CT Scans for Lung Cancer Diagnosis and Prognosis Prediction.

Purpose To develop a self-supervised chest CT foundation model and evaluate its performance in lung cancer clinical tasks. Materials and Methods In th...

Simultaneous synthesis of perfusion and ventilation images from CT using a dual-decoder residual attention network for lung disease diagnosis.

BACKGROUND: Deep learning algorithms can synthesize pulmonary functional images from CT images. However, previous studies have only been able to predi...

Generalizability of deep learning-based dose conversion model in proton beam therapy.

BACKGROUND: In proton beam therapy (PBT), the analytical pencil beam (PB) algorithm involves dose uncertainties in inhomogeneous regions, making accur...

Image quality restoration in 15-s breath-hold PET using a diffusion-based neural network.

BACKGROUND: Breath-hold PET imaging helps reduce respiratory motion artifacts in thoracoabdominal scans. However, its clinical application is limited ...

Multidimensional cfRNA response modeling identifies a 5-gene pair signature for high-robust pulmonary tuberculosis diagnosis.

Lack of non-invasive biomarkers hinders pulmonary tuberculosis (PTB) management. We developed a multidimensional machine learning framework to systema...

An interpretable molecular descriptor for machine learning predictions in atmospheric science.

The study of aerosol formation and chemistry using machine learning is limited by the lack of molecular descriptors suited to atmospheric compounds. I...

Targeted inhibition of RGS19 alleviates renal fibrosis by restoring autophagy and modulating immune cell infiltration.

Renal fibrosis, a progressive pathological feature of chronic kidney disease (CKD), is driven by impaired autophagic processes and persistent immune a...

Skin-Interfaced Wireless Biomechanical System for Detecting Aspiration in Elderly Populations.

Aspiration is prevalent in the elderly population, and can lead to life-threatening conditions such as suffocation and aspiration pneumonia. However, ...

Machine Learning-Informed Nano Co-Assembly Inhibits Fibroblast Activation Protein and Improves Drug Delivery in Fibrotic Tissue.

Nanoparticle-based drug delivery faces persistent challenges, including complex fabrication processes and limited lesional accumulation. Here we intro...

The regional landscape of the human colon culturome in health and cystic fibrosis.

UNLABELLED: Cystic fibrosis (CF) alters gut physiology, yet its impact on microbial communities across colonic regions (ascending, transverse, descend...

Identification of key clinical features for pediatric respiratory syncytial virus infection using machine learning.

Fcer1g and St3gal1: Macrophage-associated angiogenesis biomarkers and therapeutic targets in sepsis-induced acute lung injury.

BACKGROUND: Acute lung injury (ALI) involves the release of growth factors and inflammatory mediators from damaged pulmonary tissues, fostering endoth...

Distinguishing post-COVID from long-COVID in adults: Development and validation of a biomarker signature using targeted proteomics and machine learning in a cross-sectional observational study.

BACKGROUND: COVID-19 can have diverse clinical manifestations, ranging from asymptomatic infection to critical illness with multiorgan involvement. Wh...

Integrated machine learning risk model for predicting radiation pneumonitis in lung cancer patients with interstitial lung disease.

BACKGROUND: Radiation pneumonitis (RP) is a serious complication in lung cancer patients with pre-existing interstitial lung disease (ILD) undergoing ...

Acute respiratory infection (COVID-19) risk prediction in travelers: A random forest model.

BACKGROUND: Early screening during outbreaks of acute respiratory infections (ARIs) is critical for controlling disease spread among international tra...

Data-driven model analysis of the impact of environmental and socioeconomic factors on tuberculosis incidence.

Tuberculosis (TB), a global infectious disease, poses a formidable challenge to Taiwan, China, exacerbated by its aging demographic and the incursion ...

A multi-omics analysis integrating mendelian randomization, brain functional connectivity, and transcriptomics to explore risk-associated features in non-small cell lung cancer.

BACKGROUND: NSCLC remains one of the leading causes of death from cancer worldwide. Although brain metastases are indeed common and also a significant...