Pulmonology

Prognostic Value and Reproducibility of AI-assisted Analysis of Lung Involvement in COVID-19 on Low-Dose Submillisievert Chest CT: Sample Size Implications for Clinical Trials.

PURPOSE: To compare the prognostic value and reproducibility of visual versus AI-assisted analysis o...

2019 Novel Coronavirus-Infected Pneumonia on CT: A Feasibility Study of Few-Shot Learning for Computerized Diagnosis of Emergency Diseases.

COVID-19 is an emerging disease with transmissibility and severity. So far, there are no effective t...

Effect of Obesity on Clinical Outcomes of Patients Treated With Cefepime.

As the prevalence of obesity climbs, dosing of antimicrobials, particularly cephalosporins, is beco...

Content-Based Image Retrieval of Chest CT with Convolutional Neural Network for Diffuse Interstitial Lung Disease: Performance Assessment in Three Major Idiopathic Interstitial Pneumonias.

OBJECTIVE: To assess the performance of content-based image retrieval (CBIR) of chest CT for diffuse...

Relationship between Firefighter Physical Fitness and Special Ability Performance: Predictive Research Based on Machine Learning Algorithms.

Firefighters require a high level of physical fitness to meet the demands of their job. The correlat...

Lung Shrinkage: An Additional CT Marker in the Follow-up of Fibrotic Interstitial Lung Disease.

Elastic Registration-driven Deep Learning for Longitudinal Assessment of Systemic Sclerosis Interstitial Lung Disease at CT.

Background Longitudinal follow-up of interstitial lung diseases (ILDs) at CT mainly relies on the ev...

Chest x-ray analysis with deep learning-based software as a triage test for pulmonary tuberculosis: a prospective study of diagnostic accuracy for culture-confirmed disease.

BACKGROUND: Deep learning-based radiological image analysis could facilitate use of chest x-rays as ...

Predicting Deep Learning Based Multi-Omics Parallel Integration Survival Subtypes in Lung Cancer Using Reverse Phase Protein Array Data.

Mortality attributed to lung cancer accounts for a large fraction of cancer deaths worldwide. With i...

Predicting antimicrobial resistance using conserved genes.

A growing number of studies are using machine learning models to accurately predict antimicrobial re...

A multi-task pipeline with specialized streams for classification and segmentation of infection manifestations in COVID-19 scans.

We are concerned with the challenge of coronavirus disease (COVID-19) detection in chest X-ray and C...

Development of a prognostic model for mortality in COVID-19 infection using machine learning.

Coronavirus disease 2019 (COVID-19) is a novel disease resulting from infection with severe acute re...

AI-driven quantification, staging and outcome prediction of COVID-19 pneumonia.

Coronavirus disease 2019 (COVID-19) emerged in 2019 and disseminated around the world rapidly. Compu...

CoLe-CNN: Context-learning convolutional neural network with adaptive loss function for lung nodule segmentation.

BACKGROUND AND OBJECTIVE: An accurate segmentation of lung nodules in computed tomography images is ...

Extracting Lungs from CT Images via Deep Convolutional Neural Network Based Segmentation and Two-Pass Contour Refinement.

Lung segmentation is a key step of thoracic computed tomography (CT) image processing, and it plays ...

Reproducibility of abnormality detection on chest radiographs using convolutional neural network in paired radiographs obtained within a short-term interval.

We evaluated the reproducibility of computer-aided detections (CADs) with a convolutional neural net...

Diagnosis of common pulmonary diseases in children by X-ray images and deep learning.

Acute lower respiratory infection is the leading cause of child death in developing countries. Curre...

Dyspnea, effort and muscle pain during exercise in lung transplant recipients: an analysis of their association with cardiopulmonary function parameters using machine learning.

BACKGROUND: Despite improvement in lung function, most lung transplant (LTx) recipients show an unex...

Recurrent Hemoptysis After Bronchial Artery Embolization: Prediction Using a Nomogram and Artificial Neural Network Model.

The purpose of this study was to develop an effective nomogram and artificial neural network (ANN) ...

Combination of Deep Learning-Based Denoising and Iterative Reconstruction for Ultra-Low-Dose CT of the Chest: Image Quality and Lung-RADS Evaluation.

The objective of our study was to assess the effect of the combination of deep learning-based denoi...

The in vitro toxicity evaluation of halloysite nanotubes (HNTs) in human lung cells.

Halloysite nanotubes (HNTs) have been increasingly used in many industrial and biomedical fields. Th...