AIMC Topic: Pleural Effusion
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Classification of pleural effusions using deep learning visual models: contrastive-loss.
Scientific reports
Apr 1, 2022
Blood and fluid analysis is extensively used for classifying the etiology of pleural effusion. However, most studies focused on determining the presence of a disease. This study classified pleural effusion etiology employing deep learning models by a...
CheXED: Comparison of a Deep Learning Model to a Clinical Decision Support System for Pneumonia in the Emergency Department.
Journal of thoracic imaging
Sep 23, 2021
PURPOSE: Patients with pneumonia often present to the emergency department (ED) and require prompt diagnosis and treatment. Clinical decision support systems for the diagnosis and management of pneumonia are commonly utilized in EDs to improve patien...
Automatic deep learning-based pleural effusion classification in lung ultrasound images for respiratory pathology diagnosis.
Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
Mar 8, 2021
Lung ultrasound (LUS) imaging as a point-of-care diagnostic tool for lung pathologies has been proven superior to X-ray and comparable to CT, enabling earlier and more accurate diagnosis in real-time at the patient's bedside. The main limitation to w...
Automated analysis and detection of abnormalities in transaxial anatomical cardiovascular magnetic resonance images: a proof of concept study with potential to optimize image acquisition.
The international journal of cardiovascular imaging
Oct 29, 2020
The large number of available MRI sequences means patients cannot realistically undergo them all, so the range of sequences to be acquired during a scan are protocolled based on clinical details. Adapting this to unexpected findings identified early ...
Deep learning-based detection system for multiclass lesions on chest radiographs: comparison with observer readings.
European radiology
Nov 20, 2019
OBJECTIVE: To investigate the feasibility of a deep learning-based detection (DLD) system for multiclass lesions on chest radiograph, in comparison with observers.
Identifying tuberculous pleural effusion using artificial intelligence machine learning algorithms.
Respiratory research
Oct 16, 2019
BACKGROUND: The differential diagnosis of tuberculous pleural effusion (TPE) is challenging. In recent years, artificial intelligence (AI) machine learning algorithms have started being used to an increasing extent in disease diagnosis due to the hig...
The comparison of pleural fluid TNF-α levels in tuberculous and nontuberculous pleural effusion.
The Indian journal of tuberculosis
Jun 8, 2018
BACKGROUND: Tuberculous pleural effusion is the manifestation of Mycobacterium tuberculosis infection in pleura. With existing means, it is difficult to establish the diagnosis of tuberculosis (TB) and non-TB pleural effusions; thus, establishing the...
Machine learning-based Diagnostic model for determining the etiology of pleural effusion using Age, ADA and LDH.
Respiratory research
May 2, 2025
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...
Machine Learning Model Predictors of Intrapleural Tissue Plasminogen Activator and DNase Failure in Pleural Infection: A Multicenter Study.
Annals of the American Thoracic Society
Feb 1, 2025
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...
Interpretable noninvasive diagnosis of tuberculous pleural effusion using LGBM and SHAP: development and clinical application of a machine learning model.
PeerJ
Jan 1, 2025
BACKGROUND: Tuberculous pleural effusion (TPE) is a prevalent tuberculosis complication, with diagnosis presenting considerable challenges. Timely and precise identification of TPE is vital for effective patient management and prognosis, yet existing...
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