Pulmonology

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

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AI in predicting COPD in the Canadian population.

Chronic obstructive pulmonary disease (COPD) is a progressive lung disease that produces non-reversi...

Machine Learning-Based HIV Risk Estimation Using Incidence Rate Ratios.

HIV/AIDS is an ongoing global pandemic, with an estimated 39 million infected worldwide. Early detec...

Preclinical Evaluation of a New ECCO2R Setup.

Low flow extracorporeal carbon dioxide removal (ECCO2R) is a promising approach to correct hypercapn...

Validation of expert system enhanced deep learning algorithm for automated screening for COVID-Pneumonia on chest X-rays.

SARS-CoV2 pandemic exposed the limitations of artificial intelligence based medical imaging systems....

RespiraTox - Development of a QSAR model to predict human respiratory irritants.

Respiratory irritation is an important human health endpoint in chemical risk assessment. There are ...

Automatic Inter-Frame Patient Motion Correction for Dynamic Cardiac PET Using Deep Learning.

Patient motion during dynamic PET imaging can induce errors in myocardial blood flow (MBF) estimatio...

Nursing Intervention Countermeasures of Robot-Assisted Laparoscopic Urological Surgery Complications.

The objective is to explore the application effect of comprehensive nursing intervention in preventi...

Creating a training set for artificial intelligence from initial segmentations of airways.

Airways segmentation is important for research about pulmonary disease but require a large amount of...

Enhanced antibacterial activity of acid treated MgO nanoparticles on .

Acid treatment is one of the effective methods that directly modifies surface physical and chemical ...

Development of a Machine learning image segmentation-based algorithm for the determination of the adequacy of Gram-stained sputum smear images.

BACKGROUND: Machine learning (ML) prepares and trains a model through supervised or unsupervised lea...

An end-to-end approach to segmentation in medical images with CNN and posterior-CRF.

Conditional Random Fields (CRFs) are often used to improve the output of an initial segmentation mod...

Anatomically informed deep learning on contrast-enhanced cardiac magnetic resonance imaging for scar segmentation and clinical feature extraction.

BACKGROUND: Visualizing fibrosis on cardiac magnetic resonance (CMR) imaging with contrast enhanceme...

A comparative study of auto-contouring softwares in delineation of organs at risk in lung cancer and rectal cancer.

Radiotherapy requires the target area and the organs at risk to be contoured on the CT image of the ...

Direct pixel to pixel principal strain mapping from tagging MRI using end to end deep convolutional neural network (DeepStrain).

Regional soft tissue mechanical strain offers crucial insights into tissue's mechanical function and...

Diagnostic Value of Deep Learning-Based CT Feature for Severe Pulmonary Infection.

The study aimed to explore the diagnostic value of computed tomography (CT) images based on cavity c...

Development of a machine learning model using electrocardiogram signals to improve acute pulmonary embolism screening.

AIMS: Clinical scoring systems for pulmonary embolism (PE) screening have low specificity and contri...

A Novel and Robust Approach to Detect Tuberculosis Using Transfer Learning.

Deep learning has emerged as a promising technique for a variety of elements of infectious disease m...

Performance of a deep learning-based lung nodule detection system as an alternative reader in a Chinese lung cancer screening program.

OBJECTIVE: To evaluate the performance of a deep learning-based computer-aided detection (DL-CAD) sy...

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