Pulmonology

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

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Updated perspectives on visceral pleural invasion in non-small cell lung cancer: A propensity score-matched analysis of the SEER database.

BACKGROUND: Visceral pleural invasion (VPI), including PL1 (the tumor invades beyond the elastic lay...

Diagnostic MicroRNA Signatures to Support Classification of Pulmonary Hypertension.

BACKGROUND: Patients with pulmonary hypertension (PH) are classified based on disease pathogenesis a...

Hierarchical embedding attention for overall survival prediction in lung cancer from unstructured EHRs.

The automated processing of Electronic Health Records (EHRs) poses a significant challenge due to th...

Applications of machine learning approaches for pediatric asthma exacerbation management: a systematic review.

BACKGROUND: Pediatric asthma is a common chronic respiratory disease worldwide, and its acute exacer...

A machine learning-based severity stratification tool for high altitude pulmonary edema.

This study aimed to identify key predictors for the severity of High Altitude Pulmonary Edema (HAPE)...

Predicting mortality and risk factors of sepsis related ARDS using machine learning models.

Sepsis related acute respiratory distress syndrome (ARDS) is a common and serious disease in clinic....

Artificial Intelligence Models for Pediatric Lung Sound Analysis: Systematic Review and Meta-Analysis.

BACKGROUND: Pediatric respiratory diseases, including asthma and pneumonia, are major causes of morb...

Detection and prediction of real-world severe asthma phenotypes by application of machine learning to electronic health records.

BACKGROUND: Asthma is a heterogeneous disease with a diverse array of phenotypes that differ in infl...

EffiCOVID-net: A highly efficient convolutional neural network for COVID-19 diagnosis using chest X-ray imaging.

The global COVID-19 pandemic has drastically affected daily life, emphasizing the urgent need for ea...

Predicting lung cancer bone metastasis using CT and pathological imaging with a Swin Transformer model.

Bone metastasis is a common and serious complication in lung cancer patients, leading to severe pain...

The role and machine learning analysis of mitochondrial autophagy-related gene expression in lung adenocarcinoma.

OBJECTIVE: Lung adenocarcinoma (LUAD) continues to be a primary cause of cancer-related mortality gl...

Tuberculosis detection using few shot learning.

Tuberculosis (TB), a contagious disease, significantly affects lungs functioning. Amongst multiple d...

Development and validation of multi-center serum creatinine-based models for noninvasive prediction of kidney fibrosis in chronic kidney disease.

OBJECTIVE: Kidney fibrosis is a key pathological feature in the progression of chronic kidney diseas...

Single-Cell Sequencing-Guided Annotation of Rare Tumor Cells for Deep Learning-Based Cytopathologic Diagnosis of Early Lung Cancer.

Deep learning (DL) models for medical image analysis are majorly bottlenecked by the lack of well-an...

Diagnosis accuracy of machine learning for idiopathic pulmonary fibrosis: a systematic review and meta-analysis.

BACKGROUND: The diagnosis of idiopathic pulmonary fibrosis (IPF) is complex, which requires lung bio...

Prediction of postoperative intensive care unit admission with artificial intelligence models in non-small cell lung carcinoma.

BACKGROUND: There is no standard practice for intensive care admission after non-small cell lung can...

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