Pulmonology

Machine learning in pulmonary carcinoid prognostication: A critical appraisal.

Diagnostic tools in respiratory medicine (Review).

Recent advancements in diagnostic technologies have significantly transformed the landscape of respiratory medicine, aiming for early detection, improved specificity and personalized therapeutic strategies. Innovations in imaging such as multi-slice computed tomography (CT) scanners, high-resolution CT and magnetic resonance imaging (MRI) have revolutionized our ability to visualize and assess the...

Trustworthy AI for stage IV non-small cell lung cancer: Automatic segmentation and uncertainty quantification.

Accurate segmentation of lung tumors is essential for advancing personalized medicine in non-small cell lung cancer (NSCLC). However, stage IV NSCLC p...

Meta-analysis of AI-based pulmonary embolism detection: How reliable are deep learning models?

RATIONALE AND OBJECTIVES: Deep learning (DL)-based methods show promise in detecting pulmonary embolism (PE) on CT pulmonary angiography (CTPA), poten...

Machine learning in biofluid mechanics: A review of recent developments.

This review paper comprehensively examines recent advancements in machine learning (ML) applications within biofluid mechanics, with a targeted focus ...

Ultra-low-power System-on-Chip for automated screening of central apnea and hypopnea via chin electromyography.

Central Apnea (CA) and Central Hypopnea (CH) are sleep disorders arising from the brain's inability to signal respiratory muscles, potentially leading...

Multimodal AI framework for lung cancer diagnosis: Integrating CNN and ANN models for imaging and clinical data analysis.

Lung cancer remains a leading cause of cancer-related mortality worldwide, emphasizing the critical need for accurate and early diagnostic solutions. ...

Wet and dry cough classification using cough sound characteristics and machine learning: A systematic review.

BACKGROUND: Distinguishing between productive (wet) and non-productive (dry) cough types is important for evaluating respiratory health, assisting in ...

Single-shot, receptor-free, rapid detection and classification of five respiratory viruses by machine learning integrated SERS sensing platform.

A machine learning integrated SERS sensing platform is developed for a single-shot, receptor-free, rapid detection and classification of five respirat...

Artificial intelligence applications for the diagnosis of pulmonary nodules.

PURPOSE OF REVIEW: This review evaluates the role of artificial intelligence (AI) in diagnosing solitary pulmonary nodules (SPNs), focusing on clinica...

Artificial Intelligence-assisted Pixel-level Lung (APL) Scoring for Fast and Accurate Quantification in Ultra-short Echo-time MRI

Lung magnetic resonance imaging (MRI) with ultrashort echo-time (UTE) represents a recent breakthrough in lung structure imaging, providing image re...

BPD-Neo: An MRI Dataset for Lung-Trachea Segmentation with Clinical Data for Neonatal Bronchopulmonary Dysplasia

Bronchopulmonary dysplasia (BPD) is a common complication among preterm neonates, with portable X-ray imaging serving as the standard diagnostic mod...

High Resolution Isotropic 3D Cine imaging with Automated Segmentation using Concatenated 2D Real-time Imaging and Deep Learning

Background: Conventional cardiovascular magnetic resonance (CMR) in paediatric and congenital heart disease uses 2D, breath-hold, balanced steady st...

DIGS: Dynamic CBCT Reconstruction using Deformation-Informed 4D Gaussian Splatting and a Low-Rank Free-Form Deformation Model

3D Cone-Beam CT (CBCT) is widely used in radiotherapy but suffers from motion artifacts due to breathing. A common clinical approach mitigates this ...

Extracting True Virus SERS Spectra and Augmenting Data for Improved Virus Classification and Quantification.

Surface-enhanced Raman spectroscopy (SERS) is a transformative tool for infectious disease diagnostics, offering rapid and sensitive species identific...

MedPrompt: LLM-CNN Fusion with Weight Routing for Medical Image Segmentation and Classification

Current medical image analysis systems are typically task-specific, requiring separate models for classification and segmentation, and lack the flex...

AI-assisted radiographic analysis in detecting alveolar bone-loss severity and patterns

Periodontitis, a chronic inflammatory disease causing alveolar bone loss, significantly affects oral health and quality of life. Accurate assessment...

[Application of multi-scale spatiotemporal networks in physiological signal and facial action unit measurement].

Multi-task learning (MTL) has demonstrated significant advantages in the field of physiological signal measurement. This approach enhances the model's...

Bibliometric analysis of research on spinal tuberculosis in last 5 years.

BACKGROUND: Spinal tuberculosis (TB), also known as Pott's spine, remains a significant global health issue, particularly in regions with a high TB bu...

Deep learning-based forecasting of daily maximum ozone levels and assessment of socioeconomic and health impacts in South Korea.

Accurate forecasting of ground-level ozone (O) is essential for assessing its public health and socioeconomic impacts. This study evaluates the perfor...