Pulmonology

Latest AI and machine learning research in pulmonology for healthcare professionals.

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Exploratory cluster analysis of IL2Ra and associated biomarkers and complications after blunt chest trauma.

BACKGROUND: Rib fractures compromise approximately 40% of all fractures in the United States. Despit...

Development and validation of a nomogram model of lung metastasis in breast cancer based on machine learning algorithm and cytokines.

BACKGROUND: The relationship between cytokines and lung metastasis (LM) in breast cancer (BC) remain...

Explainable AI for lung cancer detection via a custom CNN on CT images.

Lung cancer, which claims 1.8 million lives annually, is still one of the leading causes of cancer-r...

Tumor-educated platelets in lung cancer.

Non-invasive diagnostic monitoring techniques have become essential for treating lung cancer (LC), w...

Radiomics for lung cancer diagnosis, management, and future prospects.

Lung cancer remains the leading cause of cancer-related mortality worldwide, with its early detectio...

A comparison of an integrated and image-only deep learning model for predicting the disappearance of indeterminate pulmonary nodules.

BACKGROUND: Indeterminate pulmonary nodules (IPNs) require follow-up CT to assess potential growth; ...

Machine learning-based integration reveals reliable biomarkers and potential mechanisms of NASH progression to fibrosis.

Non-alcoholic fatty liver disease (NAFLD) affects about 25% of adults worldwide. Its advanced form, ...

Detecting arousals and sleep from respiratory inductance plethysmography.

PURPOSE: Accurately identifying sleep states (REM, NREM, and Wake) and brief awakenings (arousals) i...

The role of machine learning in predicting titanium dioxide nanoparticles induced pulmonary pathology using transcriptomic biomarkers.

This study explores the application of machine learning (ML) in identifying transcriptomic changes a...

Machine-Learning-Based Computed Tomography Radiomics Regression Model for Predicting Pulmonary Function.

RATIONALE AND OBJECTIVES: Chest computed tomography (CT) radiomics can be utilized for categorical p...

Semi-supervised temporal attention network for lung 4D CT ventilation estimation.

Computed tomography (CT)-derived ventilation estimation, also known as CT ventilation imaging (CTVI)...

Tidal Volume Monitoring via Surface Motions of the Upper Body-A Pilot Study of an Artificial Intelligence Approach.

The measurement of tidal volumes via respiratory-induced surface movements of the upper body has bee...

Preoperative prediction of pulmonary ground-glass nodule infiltration status by CT-based radiomics combined with neural networks.

OBJECTIVE: The infiltration status of pulmonary ground-glass nodules (GGNs) exhibits significant var...

Clinical subtypes identification and feature recognition of sepsis leukocyte trajectories based on machine learning.

Sepsis is a highly variable condition, and tracking leukocyte patterns may offer insights for tailor...

Lung nodule detection using a multi-scale convolutional neural network and global channel spatial attention mechanisms.

Early detection of lung nodules is crucial for the prevention and treatment of lung cancer. However,...

MLG2Net: Molecular Global Graph Network for Drug Response Prediction in Lung Cancer Cell Lines.

Drug response prediction (DRP) is a central task in the era of precision medicine. Over the past dec...

Deep-Learning-Assisted Microfluidic Immunoassay via Smartphone-Based Imaging Transcoding System for On-Site and Multiplexed Biosensing.

Point-of-care testing (POCT) with multiplexed capability, ultrahigh sensitivity, affordable smart de...

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