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Pleural Effusion, Malignant

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The comparison of pleural fluid TNF-α levels in tuberculous and nontuberculous pleural effusion.

The Indian journal of tuberculosis
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
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...

[Diagnosis of malignant pleural effusions using convolutional neural networks by the morphometric image analysis of facies of pleural exudate].

Khirurgiia
OBJECTIVE: To estimate the possibility of diagnosis of malignant pleural effusion using convolutional neural networks of facies images of pleural exudates obtained by the method of wedge-shaped dehydration.

Machine learning applied to near-infrared spectra for clinical pleural effusion classification.

Scientific reports
Lung cancer patients with malignant pleural effusions (MPE) have a particular poor prognosis. It is crucial to distinguish MPE from benign pleural effusion (BPE). The present study aims to develop a rapid, convenient and economical diagnostic method ...

Deep learning for diagnosis of malign pleural effusion on computed tomography images.

Clinics (Sao Paulo, Brazil)
BACKGROUND: The pleura is a serous membrane that surrounds the lungs. The visceral surface secretes fluid into the serous cavity and the parietal surface ensures a regular absorption of this fluid. If this balance is disturbed, fluid accumulation occ...

Deep Learning-Based Computational Cytopathologic Diagnosis of Metastatic Breast Carcinoma in Pleural Fluid.

Cells
A Pleural effusion cytology is vital for treating metastatic breast cancer; however, concerns have arisen regarding the low accuracy and inter-observer variability in cytologic diagnosis. Although artificial intelligence-based image analysis has show...

Diagnostic utility of transfer learning by using convolutional neural network for cytological diagnosis of malignant effusions.

Diagnostic cytopathology
INTRODUCTION: Cytological analysis of effusion specimens provides critical information regarding the diagnosis and staging of malignancies, thus guiding their treatment and subsequent monitoring. Keeping in view the challenges encountered in the morp...

Weakly Supervised Multiple Instance Learning Model With Generalization Ability for Clinical Adenocarcinoma Screening on Serous Cavity Effusion Pathology.

Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc
Accurate and rapid screening of adenocarcinoma cells in serous cavity effusion is vital in diagnosing the stage of metastatic tumors and providing prompt medical treatment. However, it is often difficult for pathologists to screen serous cavity effus...

Development and validation of a machine learning-based nomogram for predicting prognosis in lung cancer patients with malignant pleural effusion.

Scientific reports
Malignant pleural effusion (MPE) is a common complication in patients with advanced lung cancer, significantly impacting their survival rates and quality of life. Effective tools for assessing the prognosis of these patients are urgently needed to en...