Pulmonology

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

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Automatic Detection and Classification of Lung Nodules in CT Image Using Optimized Neuro Fuzzy Classifier with Cuckoo Search Algorithm.

The Lung nodules are very important to indicate the lung cancer, and its early detection enables tim...

ECM-CSD: An Efficient Classification Model for Cancer Stage Diagnosis in CT Lung Images Using FCM and SVM Techniques.

As is eminent, lung cancer is one of the death frightening syndromes among people in present cases. ...

An effective and accurate identification system of Mycobacterium tuberculosis using convolution neural networks.

Tuberculosis (TB) remains the leading cause of morbidity and mortality from infectious disease in de...

Quantifying lung ultrasound comets with a convolutional neural network: Initial clinical results.

Lung ultrasound comets are "comet-tail" artifacts appearing in lung ultrasound images. They are part...

Improving Accuracy of Lung Nodule Classification Using Deep Learning with Focal Loss.

Early detection and classification of pulmonary nodules using computer-aided diagnosis (CAD) systems...

A Comparative Texture Analysis Based on NECT and CECT Images to Differentiate Lung Adenocarcinoma from Squamous Cell Carcinoma.

The purpose of the study was to compare the texture based discriminative performances between non-co...

Pulmonary nodule segmentation with CT sample synthesis using adversarial networks.

PURPOSE: Segmentation of pulmonary nodules is critical for the analysis of nodules and lung cancer d...

Gene fingerprint model for literature based detection of the associations among complex diseases: a case study of COPD.

BACKGROUND: Disease comorbidity is very common and has significant impact on disease treatment. Reve...

Automatic 3D Bi-Ventricular Segmentation of Cardiac Images by a Shape-Refined Multi- Task Deep Learning Approach.

Deep learning approaches have achieved state-of-the-art performance in cardiac magnetic resonance (C...

Lung and Pancreatic Tumor Characterization in the Deep Learning Era: Novel Supervised and Unsupervised Learning Approaches.

Risk stratification (characterization) of tumors from radiology images can be more accurate and fast...

Predicting radiation pneumonitis in locally advanced stage II-III non-small cell lung cancer using machine learning.

BACKGROUND AND PURPOSE: Radiation pneumonitis (RP) is a radiotherapy dose-limiting toxicity for loca...

Detection of pulmonary ground-glass opacity based on deep learning computer artificial intelligence.

BACKGROUND: A deep learning computer artificial intelligence system is helpful for early identificat...

Deep Learning Algorithms with Demographic Information Help to Detect Tuberculosis in Chest Radiographs in Annual Workers' Health Examination Data.

We aimed to use deep learning to detect tuberculosis in chest radiographs in annual workers' health ...

Automatic lung nodule detection using multi-scale dot nodule-enhancement filter and weighted support vector machines in chest computed tomography.

A novel CAD scheme for automated lung nodule detection is proposed to assist radiologists with the d...

Learning to detect chest radiographs containing pulmonary lesions using visual attention networks.

Machine learning approaches hold great potential for the automated detection of lung nodules on ches...

A Large Animal Model of Right Ventricular Failure due to Chronic Thromboembolic Pulmonary Hypertension: A Focus on Function.

Chronic thromboembolic pulmonary hypertension (CTEPH) is a debilitating disease that progresses to r...

A GIS-Based Artificial Neural Network Model for Spatial Distribution of Tuberculosis across the Continental United States.

Despite the usefulness of artificial neural networks (ANNs) in the study of various complex problems...

Gallic Acid Potentiates the Antimicrobial Activity of Tulathromycin Against Two Key Bovine Respiratory Disease (BRD) Causing-Pathogens.

Bovine respiratory disease (BRD) is the most common infectious disease in dairy and beef cattle. It ...

Segmentation of lung parenchyma in CT images using CNN trained with the clustering algorithm generated dataset.

BACKGROUND: Lung segmentation constitutes a critical procedure for any clinical-decision supporting ...

Classification and Quantification of Emphysema Using a Multi-Scale Residual Network.

Automated tissue classification is an essential step for quantitative analysis and treatment of emph...

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