Pulmonology

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

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Detecting pulmonary malignancy against benign nodules using noninvasive cell-free DNA fragmentomics assay.

BACKGROUND: Early screening using low-dose computed tomography (LDCT) can reduce mortality caused by...

CT-based deep learning radiomics biomarker for programmed cell death ligand 1 expression in non-small cell lung cancer.

BACKGROUND: Programmed cell death ligand 1 (PD-L1), as a reliable predictive biomarker, plays an imp...

Predicting Tracheostomy Need on Admission to the Intensive Care Unit-A Multicenter Machine Learning Analysis.

OBJECTIVE: It is difficult to predict which mechanically ventilated patients will ultimately require...

Predictive modeling of mortality in carbapenem-resistant bloodstream infections using machine learning.

, a notable drug-resistant bacterium, often induces severe infections in healthcare settings, prompt...

The impact of high-order features on performance of radiomics studies in CT non-small cell lung cancer.

High-order radiomic features have been shown to produce high performance models in a variety of scen...

Performance and clinical utility of an artificial intelligence-enabled tool for pulmonary embolism detection.

PURPOSE: Diagnosing pulmonary embolism (PE) is still challenging due to other conditions that can mi...

Computer-aided prognosis of tuberculous meningitis combining imaging and non-imaging data.

Tuberculous meningitis (TBM) is the most lethal form of tuberculosis. Clinical features, such as com...

Identification of severe acute pediatric asthma phenotypes using unsupervised machine learning.

RATIONALE: More targeted management of severe acute pediatric asthma could improve clinical outcomes...

Machine-learning and scRNA-Seq-based diagnostic and prognostic models illustrating survival and therapy response of lung adenocarcinoma.

Lung cancer is a major cause accounting for cancer-related mortalities, with lung adenocarcinoma (LU...

Deep learning-based respiratory muscle segmentation as a potential imaging biomarker for respiratory function assessment.

Respiratory diseases significantly affect respiratory function, making them a considerable contribut...

Identification of eupneic breathing using machine learning.

The diaphragm muscle (DIAm) is the primary inspiratory muscle in mammals. In awake animals, consider...

Smart Sleep Monitoring: Sparse Sensor-Based Spatiotemporal CNN for Sleep Posture Detection.

Sleep quality is heavily influenced by sleep posture, with research indicating that a supine posture...

A prognostic framework for predicting lung signet ring cell carcinoma via a machine learning based cox proportional hazard model.

PURPOSE: Signet ring cell carcinoma (SRCC) is a rare type of lung cancer. The conventional survival ...

Predicting Acute Exacerbation Phenotype in Chronic Obstructive Pulmonary Disease Patients Using VGG-16 Deep Learning.

INTRODUCTION: Exacerbations of chronic obstructive pulmonary disease (COPD) have a significant impac...

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