Pulmonology

A machine learning approach to predicting dyspnea with noninvasive biomarkers.

Dyspnea is the subjective sensation of breathing discomfort. This symptom is highly prevalent in pat...

Multidimensional cortical morphological alterations in COPD using explainable machine learning.

Cognitive dysfunction is a common extrapulmonary manifestation of chronic obstructive pulmonary dise...

Accurate diagnosis of non-small cell and small cell lung cancer by using machine learning models trained with physical science features extracted from pathological images.

BACKGROUND: Accurate differentiation between non-small cell lung cancer (NSCLC) and small cell lung ...

Computed tomography in ARDS, from morphological insights to AI-powered multi-modal analysis: a narrative review.

BACKGROUND: Acute respiratory distress syndrome (ARDS) is a critical clinical condition characterize...

Deep-learning-based diagnostic models for transcutaneous oxygen pressure-defined peripheral arterial disease and lower extremity wound healing in patients with diabetic foot.

BACKGROUND: Few studies have evaluated peripheral artery disease (PAD) and wound healing in patients...

Tandem bulk oxygen diffusion and surface reactions in reducible metal oxides control redox cycle dynamics.

The interplay between bulk oxygen diffusion and surface reactions in reducible metal oxides is key i...

Phase-constrained zero-shot self-supervised learning for BLADE liver MRI reconstruction.

INTRODUCTION: Liver MRI plays a critical role in the diagnosis and monitoring of liver disease; howe...

Bacterial taxa associated with lung cancer cases in Southeast Asians: a pilot case-control study.

PURPOSE: Lung cancer is the leading cause of cancer-related mortality worldwide, yet its underlying ...

Identifying mitochondria-related signatures for tuberculosis diagnosis through machine learning on single-cell transcriptomics data and experimental verification.

Tuberculosis (TB) remains a major cause of infectious disease mortality. Early diagnosis is crucial ...

Parsimonious machine learning model to predict 1-year mortality and procedural futility after transcatheter aortic valve replacement.

BACKGROUND: Current risk scores inadequately predict long-term mortality after transcatheter aortic ...

Artificial Intelligence in Asthma: From Diagnosis to Management.

Artificial intelligence (AI) offers new opportunities to improve asthma management across the care p...

Deep learning based automated assessment of end-inspiratory pause maneuver reliability in invasive mechanical ventilation.

OBJECTIVE: Manual end-inspiratory pause maneuvers (EIPM) for plateau pressure (Pplat) measurement su...

LobePrior segments lung lobes on computed tomography images in the presence of severe abnormalities.

The development of robust algorithms for lung and lobe segmentation is essential for diagnosing and ...

A multilayer 2D material plasmonic metasurface terahertz biosensor with machine learning optimization for high-sensitivity tuberculosis detection.

Tuberculosis (TB) remains a leading global infectious disease, with over 10.6 million new cases annu...

Thrombosis after surgical splenectomy - why, in whom and can we prevent it?

Splenectomy remains a common operation performed in the setting of trauma, haematological disease, m...

Excited-State-Guided Molecular Design System for Type I Photosensitizers.

Type I photosensitizers (PSs), which generate Type I reactive oxygen species (ROS) through the elect...

S3F-Net: A Multi-Modal Approach to Medical Image Classification via Spatial-Spectral Summarizer Fusion Network.

Convolutional Neural Networks (CNNs) have become a cornerstone of medical image analysis due to thei...

Explainable deep learning-based lung cancer diagnosis using clinically-guided local interpretable model-agnostic explanations.

Lung cancer remains one of the leading causes of cancer-related deaths worldwide, highlighting the u...

Development and validation of a prediction model for respiratory complications and in-hospital mortality in trauma patients.

Intraoperative video-based artificial intelligence model exceeding surgeon accuracy for predicting severe fibrosis in minimally invasive liver surgery.

Accurate evaluation of liver fibrosis is essential for surgical planning in patients with hepatocell...

Multimodal Learning with Privileged Report Supervision for Generalizable Tuberculosis Detection on Chest Radiographs.