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Pleural Effusion

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Hepatic Hydrothorax Without Ascites: A Diagnostic And Management Challenge.

Journal of Ayub Medical College, Abbottabad : JAMC
Hepatic hydrothorax refers to the presence of a pleural effusion (usually >500 mL) in a patient with cirrhosis who does not have other reasons to have a pleural effusion (e.g., cardiac, pulmonary, or pleural disease). Hepatic hydrothorax occurs in ap...

Machine learning-based Diagnostic model for determining the etiology of pleural effusion using Age, ADA and LDH.

Respiratory research
BACKGROUND: Classification of the etiologies of pleural effusion is a critical challenge in clinical practice. Traditional diagnostic methods rely on a simple cut-off method based on the laboratory tests. However, machine learning (ML) offers a novel...

Enhanced differential evolution algorithm for feature selection in tuberculous pleural effusion clinical characteristics analysis.

Artificial intelligence in medicine
Tuberculous pleural effusion poses a significant threat to human health due to its potential for severe disease and mortality. Without timely treatment, it may lead to fatal consequences. Therefore, early identification and prompt treatment are cruci...

Deep learning model for pleural effusion detection via active learning and pseudo-labeling: a multisite study.

BMC medical imaging
BACKGROUND: The study aimed to develop and validate a deep learning-based Computer Aided Triage (CADt) algorithm for detecting pleural effusion in chest radiographs using an active learning (AL) framework. This is aimed at addressing the critical nee...

Towards Case-based Interpretability for Medical Federated Learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
We explore deep generative models to generate case-based explanations in a medical federated learning setting. Explaining AI model decisions through case-based interpretability is paramount to increasing trust and allowing widespread adoption of AI i...

Diagnostic accuracy of an automated classifier for the detection of pleural effusions in patients undergoing lung ultrasound.

The American journal of emergency medicine
RATIONALE: Lung ultrasound, the most precise diagnostic tool for pleural effusions, is underutilized due to healthcare providers' limited proficiency. To address this, deep learning models can be trained to recognize pleural effusions. However, curre...

Accuracy of Fully Automated and Human-assisted Artificial Intelligence-based CT Quantification of Pleural Effusion Changes after Thoracentesis.

Radiology. Artificial intelligence
Quantifying pleural effusion change at chest CT is important for evaluating disease severity and treatment response. The purpose of this study was to assess the accuracy of artificial intelligence (AI)-based volume quantification of pleural effusion ...

The large language model diagnoses tuberculous pleural effusion in pleural effusion patients through clinical feature landscapes.

Respiratory research
BACKGROUND: Tuberculous pleural effusion (TPE) is a challenging extrapulmonary manifestation of tuberculosis, with traditional diagnostic methods often involving invasive surgery and being time-consuming. While various machine learning and statistica...

Machine Learning Model Predictors of Intrapleural Tissue Plasminogen Activator and DNase Failure in Pleural Infection: A Multicenter Study.

Annals of the American Thoracic Society
Intrapleural enzyme therapy (IET) with tissue plasminogen activator (tPA) and DNase has been shown to reduce the need for surgical intervention for complicated parapneumonic effusion/empyema (CPPE/empyema). Failure of IET may lead to delayed care an...