Pulmonology

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

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A Comprehensive Review of Artificial Intelligence (AI) Applications in Pulmonary Hypertension (PH).

Pulmonary hypertension (PH) is a complex condition associated with significant morbidity and mortal...

Liver fibrosis stage classification in stacked microvascular images based on deep learning.

BACKGROUND: Monitoring fibrosis in patients with chronic liver disease (CLD) is an important managem...

An interpretable machine learning model for predicting in-hospital mortality in ICU patients with ventilator-associated pneumonia.

BACKGROUND: Ventilator-associated pneumonia (VAP) is a common nosocomial infection in ICU, significa...

Advanced AI-assisted panoramic radiograph analysis for periodontal prognostication and alveolar bone loss detection.

BACKGROUND: Periodontitis is a chronic inflammatory disease affecting the gingival tissues and suppo...

Anti-ceramide antibody and sphingosine-1-phosphate as potential biomarkers of unresectable non-small cell lung cancer.

OBJECTIVES: Spingosine-1-phosphate (S1P) and ceramides are bioactive sphingolipids that influence ca...

Harnessing artificial intelligence in sepsis care: advances in early detection, personalized treatment, and real-time monitoring.

Sepsis remains a leading cause of morbidity and mortality worldwide due to its rapid progression and...

Accurate identification of snoRNA targets using variational graph autoencoder to advance the redevelopment of traditional medicines.

Existing studies indicate that dysregulation or abnormal expression of small nucleolar RNA (snoRNA) ...

High performance COVID-19 screening using machine learning.

Since the World Health Organization declared the Coronavirus Disease 2019 (COVID-19) pandemic as an ...

Prediction of real-time cine-MR images during MRI-guided radiotherapy of liver cancer using a GAN-ConvLSTM network.

BACKGROUND: Respiratory motion during radiotherapy (RT) may reduce the therapeutic effect and increa...

Prediction of pulmonary embolism by an explainable machine learning approach in the real world.

In recent years, large amounts of researches showed that pulmonary embolism (PE) has become a common...

Assessing the feasibility and external validity of natural language processing-extracted data for advanced lung cancer patients.

BACKGROUND: Manual extraction of real-world clinical data for research can be time-consuming and pro...

Evaluation of an enhanced ResNet-18 classification model for rapid On-site diagnosis in respiratory cytology.

OBJECTIVE: Rapid on-site evaluation (ROSE) of respiratory cytology specimens is a critical technique...

Common biomarkers of idiopathic pulmonary fibrosis and systemic sclerosis based on WGCNA and machine learning.

Interstitial lung disease (ILD) is known to be a major complication of systemic sclerosis (SSc) and ...

Machine learning-assisted construction of COPD self-evaluation questionnaire (COPD-EQ): a national multicentre study in China.

BACKGROUND: Approximately 70% of chronic obstructive pulmonary disease (COPD) is underdiagnosed worl...

Explainable Machine Learning to Predict Treatment Response in Advanced Non-Small Cell Lung Cancer.

PURPOSE: Immune checkpoint inhibitors (ICIs) have demonstrated promise in the treatment of various c...

Bioequivalence study of fluticasone propionate nebuliser suspensions in healthy Chinese subjects.

BACKGROUND: Fluticasone propionate is a synthetic trifluoro-substituted glucocorticoid, a highly sel...

Non-invasive ML methods for diagnosis of congenital heart disease associated with pulmonary arterial hypertension.

OBJECTIVE: Congenital heart disease with pulmonary arterial hypertension (CHD-PAH), caused by CHD, i...

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