Pneumonia

Aspect Based Twitter Sentiment Analysis on Vaccination and Vaccine Types in COVID-19 Pandemic With Deep Learning.

Due to the COVID-19 pandemic, vaccine development and community vaccination studies are carried out all over the world. At this stage, the opposition to the vaccine seen in the society or the lack of trust in the developed vaccine is an important factor hampering vaccination activities. In this study, aspect-base sentiment analysis was conducted for USA, U.K., Canada, Turkey, France, Germany, Spai...

MHA-CoroCapsule: Multi-Head Attention Routing-Based Capsule Network for COVID-19 Chest X-Ray Image Classification.

The outbreak of COVID-19 threatens the lives and property safety of countless people and brings a tremendous pressure to health care systems worldwide. The principal challenge in the fight against this disease is the lack of efficient detection methods. AI-assisted diagnosis based on deep learning can detect COVID-19 cases for chest X-ray images automatically, and also improve the accuracy and eff...

Ontology-aware deep learning enables ultrafast and interpretable source tracking among sub-million microbial community samples from hundreds of niches.

The taxonomic structure of microbial community sample is highly habitat-specific, making source tracking possible, allowing identification of the nich...

Comparison of radiologist versus natural language processing-based image annotations for deep learning system for tuberculosis screening on chest radiographs.

Although natural language processing (NLP) can rapidly extract disease labels from radiology reports to create datasets for deep learning models, this...

Pediatric chest radiograph interpretation: how far has artificial intelligence come? A systematic literature review.

Most artificial intelligence (AI) studies have focused primarily on adult imaging, with less attention to the unique aspects of pediatric imaging. The...

Study on transfer learning capabilities for pneumonia classification in chest-x-rays images.

BACKGROUND: over the last year, the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) and its variants have highlighted the importance of s...

Assessing clinical applicability of COVID-19 detection in chest radiography with deep learning.

The coronavirus disease 2019 (COVID-19) pandemic has impacted healthcare systems across the world. Chest radiography (CXR) can be used as a complement...

CADxReport: Chest x-ray report generation using co-attention mechanism and reinforcement learning.

BACKGROUND: Automated generation of radiological reports for different imaging modalities is essentially required to smoothen the clinical workflow an...

A Principal Neighborhood Aggregation-Based Graph Convolutional Network for Pneumonia Detection.

Pneumonia is one of the main causes of child mortality in the world and has been reported by the World Health Organization (WHO) to be the cause of on...

Robot-enhanced diabetes care for middle-aged and older adults living with diabetes in the community: A small sample size mixed-method evaluation.

PURPOSE: This study assessed robot-enhanced healthcare in practical settings for the purpose of community diabetes care.

COVID Detection From Chest X-Ray Images Using Multi-Scale Attention.

Deep learning based methods have shown great promise in achieving accurate automatic detection of Coronavirus Disease (covid) - 19 from Chest X-Ray (c...

Deep learning of chest X-rays can predict mechanical ventilation outcome in ICU-admitted COVID-19 patients.

The COVID-19 pandemic repeatedly overwhelms healthcare systems capacity and forced the development and implementation of triage guidelines in ICU for ...

Deep Learning-Based Automatic CT Quantification of Coronavirus Disease 2019 Pneumonia: An International Collaborative Study.

OBJECTIVE: We aimed to develop and validate the automatic quantification of coronavirus disease 2019 (COVID-19) pneumonia on computed tomography (CT) ...

Predicting Usual Interstitial Pneumonia Histopathology From Chest CT Imaging With Deep Learning.

BACKGROUND: Idiopathic pulmonary fibrosis (IPF) is a progressive, often fatal form of interstitial lung disease (ILD) characterized by the absence of ...

External COVID-19 Deep Learning Model Validation on ACR AI-LAB: It's a Brave New World.

PURPOSE: Deploying external artificial intelligence (AI) models locally can be logistically challenging. We aimed to use the ACR AI-LAB software platf...

COVID-CCD-Net: COVID-19 and colon cancer diagnosis system with optimized CNN hyperparameters using gradient-based optimizer.

Coronavirus disease-2019 (COVID-19) is a new types of coronavirus which have turned into a pandemic within a short time. Reverse transcription-polymer...

An Interpretable Chest CT Deep Learning Algorithm for Quantification of COVID-19 Lung Disease and Prediction of Inpatient Morbidity and Mortality.

RATIONALE AND OBJECTIVES: The burden of coronavirus disease 2019 (COVID-19) airspace opacities is time consuming and challenging to quantify on comput...

Think positive: An interpretable neural network for image recognition.

The COVID-19 pandemic is an ongoing pandemic and is placing additional burden on healthcare systems around the world. Timely and effectively detecting...

Tracking and predicting COVID-19 radiological trajectory on chest X-rays using deep learning.

Radiological findings on chest X-ray (CXR) have shown to be essential for the proper management of COVID-19 patients as the maximum severity over the ...

Evaluation of the humoral response induced by BBIBP-CorV vaccine by determining neutralizing antibodies in peruvian healthcare personnel.

OBJECTIVE.: To determine the titer of antibodies against the receptor binding domain (RBD) of the spike protein (S) in health personnel between the 4t...