Pulmonology

Lung Nodule Detectability of Artificial Intelligence-assisted CT Image Reading in Lung Cancer Screening.

BACKGROUND: Artificial Intelligence (AI)-based automatic lung nodule detection system improves the detection rate of nodules. It is important to evaluate the clinical value of the AI system by comparing AI-assisted nodule detection with actual radiology reports.

Impact of Cystic Fibrosis Transmembrane Conductance Regulator Therapy on Chronic Rhinosinusitis and Health Status: Deep Learning CT Analysis and Patient-reported Outcomes.

Elexacaftor, tezacaftor, and ivacaftor (ETI) in triple combination improves pulmonary health for people with cystic fibrosis (PwCF). However, its impact on objective measures of sinus disease and health utility is unestablished. To evaluate the impact of ETI on chronic rhinosinusitis (CRS) and general health status incorporating computed tomography (CT), quality-of-life (QOL) and productivity lo...

A Novel Multicolor-thresholding Auto-detection Method to Detect the Location and Severity of Inflammation in Confirmed SARS-COV-2 Cases using Chest X-Ray Images.

OBJECTIVES: Since late 2019, Coronavirus Disease 2019 (COVID-19) has spread around the world. It has been determined that the disease is very contagio...

Artificial intelligence: opportunities in lung cancer.

PURPOSE OF REVIEW: In this article, we focus on the role of artificial intelligence in the management of lung cancer. We summarized commonly used algo...

Classification by a stacking model using CNN features for COVID-19 infection diagnosis.

Affecting millions of people all over the world, the COVID-19 pandemic has caused the death of hundreds of thousands of people since its beginning. Ex...

Clinical Applications of Artificial Intelligence in Positron Emission Tomography of Lung Cancer.

The ability of a computer to perform tasks normally requiring human intelligence or artificial intelligence (AI) is not new. However, until recently, ...

Computer-aided COVID-19 diagnosis and a comparison of deep learners using augmented CXRs.

BACKGROUND: Coronavirus Disease 2019 (COVID-19) is contagious, producing respiratory tract infection, caused by a newly discovered coronavirus. Its de...

UBNet: Deep learning-based approach for automatic X-ray image detection of pneumonia and COVID-19 patients.

BACKGROUND: Analysis of chest X-ray images is one of the primary standards in diagnosing patients with COVID-19 and pneumonia, which is faster than us...

The diagnostic performance of deep-learning-based CT severity score to identify COVID-19 pneumonia.

OBJECTIVE: To determine the diagnostic accuracy of a deep-learning (DL)-based algorithm using chest computed tomography (CT) scans for the rapid diagn...

Lung Cancer Detection Using Machine Learning Techniques.

Cancer has been the deadliest of diseases since decades constituting a large number of deaths annually. Lung cancer remains one of the most significan...

Digital Healthcare for Airway Diseases from Personal Environmental Exposure.

Digital technologies have emerged in various dimensions of human life, ranging from education to professional services to well-being. In particular, h...

AI-driven deep convolutional neural networks for chest X-ray pathology identification.

BACKGROUND: Chest X-ray images are widely used to detect many different lung diseases. However, reading chest X-ray images to accurately detect and cl...

Elevated Coronary Artery Calcium Quantified by a Validated Deep Learning Model From Lung Cancer Radiotherapy Planning Scans Predicts Mortality.

PURPOSE: Coronary artery calcium (CAC) quantified on computed tomography (CT) scans is a robust predictor of atherosclerotic coronary disease; however...

Relationship of MRI-measured pelvimetric dimensions and surgical positions with anaesthesia parameters in robotic perineal prostatectomy.

Theaim of this study was to determine the effect formedby pelvic diameters preoperatively measured throughmultiparametric magnetic resonance imaging (...

Deep Learning-Based Internal Target Volume (ITV) Prediction Using Cone-Beam CT Images in Lung Stereotactic Body Radiotherapy.

This study aims to develop a deep learning (DL)-based (Mask R-CNN) method to predict the internal target volume (ITV) in cone beam computed tomography...

Inferring Cell-type-specific Genes of Lung Cancer Based on Deep Learning.

BACKGROUND: Lung cancer is cancer with the highest incidence in the world, and there is obvious heterogeneity within its tumor. The emergence of singl...

Health Promotion, Health Literacy and Vaccine Hesitancy: The Role of Humanoid Robots.

The use of humanoid robot technologies within global healthcare settings is rapidly evolving; however, the potential of robots in health promotion and...

Parameter tuning in machine learning based on radiomics biomarkers of lung cancer.

BACKGROUND: Lung cancer is one of the most common cancers, and early diagnosis and intervention can improve cancer cure rate.

Developing a pneumonia diagnosis ontology from multiple knowledge sources.

Pneumonia is difficult to differentiate from other pulmonary diseases because it shares many symptoms with these diseases. Diagnosing pneumonia in cl...

A Hybrid Protocol for Identifying Comorbidity-Based Potential Drugs for COVID-19 Using Biomedical Literature Mining, Network Analysis, and Deep Learning.

Coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV2) has spread on an unprecedented scale around ...