Pulmonology

Early detection of lung cancer using artificial intelligence-enhanced optical nanosensing of chromatin alterations in field carcinogenesis.

Supranucleosomal chromatin structure, including chromatin domain conformation, is involved in the regulation of gene expression and its dysregulation has been associated with carcinogenesis. Prior studies have shown that cells in the buccal mucosa carry a molecular signature of lung cancer among the cigarette-smoking population, the phenomenon known as field carcinogenesis or field of injury. Thus...

Fully automatic deep learning-based lung parenchyma segmentation and boundary correction in thoracic CT scans.

PURPOSE: The proposed work aims to develop an algorithm to precisely segment the lung parenchyma in thoracic CT scans. To achieve this goal, the proposed technique utilized a combination of deep learning and traditional image processing algorithms. The initial step utilized a trained convolutional neural network (CNN) to generate preliminary lung masks, followed by the proposed post-processing alg...

Development and validation of a hybrid deep learning-machine learning approach for severity assessment of COVID-19 and other pneumonias.

The Coronavirus Disease 2019 (COVID-19) is transitioning into the endemic phase. Nonetheless, it is crucial to remain mindful that pandemics related t...

Automatic detection and classification of lung cancer CT scans based on deep learning and ebola optimization search algorithm.

Recently, research has shown an increased spread of non-communicable diseases such as cancer. Lung cancer diagnosis and detection has become one of th...

The International Association for the Study of Lung Cancer Early Lung Imaging Confederation Open-Source Deep Learning and Quantitative Measurement Initiative.

INTRODUCTION: With global adoption of computed tomography (CT) lung cancer screening, there is increasing interest to use artificial intelligence (AI)...

Value of deep learning reconstruction of chest low-dose CT for image quality improvement and lung parenchyma assessment on lung window.

OBJECTIVES: To explore the performance of low-dose computed tomography (LDCT) with deep learning reconstruction (DLR) for the improvement of image qua...

Chronic thromboembolic pulmonary hypertension: realising the potential of multimodal management.

Chronic thromboembolic pulmonary hypertension (CTEPH) is a rare complication of acute pulmonary embolism. Important advances have enabled better under...

Deep Learning for Predicting Effect of Neoadjuvant Therapies in Non-Small Cell Lung Carcinomas With Histologic Images.

Neoadjuvant therapies are used for locally advanced non-small cell lung carcinomas, whereby pathologists histologically evaluate the effect using rese...

Deep neural network pulmonary nodule segmentation methods for CT images: Literature review and experimental comparisons.

Automatic and accurate segmentation of pulmonary nodules in CT images can help physicians perform more accurate quantitative analysis, diagnose diseas...

Effects of secretome supplementation on interleukin-6, tumor necrosis factor-α, procalcitonin, and the length of stay in acute exacerbation COPD patients.

Acute exacerbation chronic obstructive pulmonary disease (AECOPD) is associated with significant poor survival. Mesenchymal stem cells (MSC) therapy h...

Deep learning model fusion improves lung tumor segmentation accuracy across variable training-to-test dataset ratios.

This study aimed to investigate the robustness of a deep learning (DL) fusion model for low training-to-test ratio (TTR) datasets in the segmentation ...

Remote Blood Oxygen Estimation From Videos Using Neural Networks.

Peripheral blood oxygen saturation (SpO ) is an essential indicator of respiratory functionality and received increasing attention during the COVID-19...

Machine learning-based ensemble approach in prediction of lung cancer predisposition using XRCC1 gene polymorphism.

The employment of machine learning approaches has shown promising results in predicting cancer. In the current study, polymorphisms data of five singl...

An artificial intelligence algorithm for pulmonary embolism detection on polychromatic computed tomography: performance on virtual monochromatic images.

OBJECTIVES: Virtual monochromatic images (VMI) are increasingly used in clinical practice as they improve contrast-to-noise ratio. However, due to the...

Standardized Classification of Lung Adenocarcinoma Subtypes and Improvement of Grading Assessment Through Deep Learning.

The histopathologic distinction of lung adenocarcinoma (LADC) subtypes is subject to high interobserver variability, which can compromise the optimal ...

Added value of an artificial intelligence algorithm in reducing the number of missed incidental acute pulmonary embolism in routine portal venous phase chest CT.

OBJECTIVES: The purpose of this study was to evaluate the incremental value of artificial intelligence (AI) compared to the diagnostic accuracy of rad...

Artificial intelligence-assisted repurposing of lubiprostone alleviates tubulointerstitial fibrosis.

Tubulointerstitial fibrosis (TIF) is the most prominent cause which leads to chronic kidney disease (CKD) and end-stage renal failure. Despite extensi...

Modelling biochemical oxygen demand using improved neuro-fuzzy approach by marine predators algorithm.

Biochemical oxygen demand (BOD) is one of the most important parameters used for water quality assessment. Alternative methods are essential for accur...

Correlation Between Intranodular Vessels and Tumor Invasiveness of Lung Adenocarcinoma Presenting as Ground-glass Nodules: A Deep Learning 3-Dimensional Reconstruction Algorithm-based Quantitative Analysis on Noncontrast Computed Tomography Images.

PURPOSE: To evaluate the role of quantitative features of intranodular vessels based on deep learning in distinguishing pulmonary adenocarcinoma invas...

Respiratory signal estimation for cardiac perfusion SPECT using deep learning.

BACKGROUND: Respiratory motion induces artifacts in reconstructed cardiac perfusion SPECT images. Correction for respiratory motion often relies on a ...