Pneumonia

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 significant public health issues, accounting for a substantial proportion of cancer-related deaths globally. Despite ongoing efforts to curb the instances of lung cancer, India continues to see a high number of new diagnoses each year, estimated to be 70,000. ...

Demographic Reporting in Publicly Available Chest Radiograph Data Sets: Opportunities for Mitigating Sex and Racial Disparities in Deep Learning Models.

OBJECTIVE: Data sets with demographic imbalances can introduce bias in deep learning models and potentially amplify existing health disparities. We evaluated the reporting of demographics and potential biases in publicly available chest radiograph (CXR) data sets.

Optimized chest X-ray image semantic segmentation networks for COVID-19 early detection.

BACKGROUND: Although detection of COVID-19 from chest X-ray radiography (CXR) images is faster than PCR sputum testing, the accuracy of detecting COVI...

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...

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...

Automatic Localization and Identification of Thoracic Diseases from Chest X-rays with Deep Learning.

BACKGROUND: There are numerous difficulties in using deep learning to automatically locate and identify diseases in chest X-rays (CXR). The most preva...

An interpretable multi-task system for clinically applicable COVID-19 diagnosis using CXR.

BACKGROUND: With the emergence of continuously mutating variants of coronavirus, it is urgent to develop a deep learning model for automatic COVID-19 ...

CNN Features and Optimized Generative Adversarial Network for COVID-19 Detection from Chest X-Ray Images.

Coronavirus is a RNA type virus, which makes various respiratory infections in both human as well as animals. In addition, it could cause pneumonia in...

Contribution of artificial intelligence applications developed with the deep learning method to the diagnosis of COVID-19 pneumonia on computed tomography.

INTRODUCTION: Computed tomography (CT) is an auxiliary modality in the diagnosis of the novel Coronavirus (COVID-19) disease and can guide physicians ...

Feasibility of Radiomics to Differentiate Coronavirus Disease 2019 (COVID-19) from H1N1 Influenza Pneumonia on Chest Computed Tomography: A Proof of Concept.

BACKGROUND: Chest computed tomography (CT) plays an essential role in diagnosing coronavirus disease 2019 (COVID-19). However, CT findings are often n...

Deep Learning and Binary Relevance Classification of Multiple Diseases using Chest X-Ray images.

Disease detection using chest X-ray (CXR) images is one of the most popular radiology methods to diagnose diseases through a visual inspection of abno...

Lung contour detection in Chest X-ray images using Mask Region-based Convolutional Neural Network and Adaptive Closed Polyline Searching Method.

Detection of lung contour on chest X-ray images (CXRs) is a necessary step for computer-aid medical imaging analysis. Because of the low-intensity con...

TDA-Net: Fusion of Persistent Homology and Deep Learning Features for COVID-19 Detection From Chest X-Ray Images.

Topological Data Analysis (TDA) has emerged recently as a robust tool to extract and compare the structure of datasets. TDA identifies features in dat...

Avoiding a replication crisis in deep-learning-based bioimage analysis.

Deep learning algorithms are powerful tools to analyse, restore and transform bioimaging data, increasingly used in life sciences research. These appr...

CoCoNet: an efficient deep learning tool for viral metagenome binning.

MOTIVATION: Metagenomic approaches hold the potential to characterize microbial communities and unravel the intricate link between the microbiome and ...

Application of machine learning in CT images and X-rays of COVID-19 pneumonia.

Coronavirus disease (COVID-19) has spread worldwide. X-ray and computed tomography (CT) are 2 technologies widely used in image acquisition, segmentat...

Greece used AI to curb COVID: what other nations can learn.

Automated Detection and Quantification of COVID-19 Airspace Disease on Chest Radiographs: A Novel Approach Achieving Expert Radiologist-Level Performance Using a Deep Convolutional Neural Network Trained on Digital Reconstructed Radiographs From Computed Tomography-Derived Ground Truth.

OBJECTIVES: The aim of this study was to leverage volumetric quantification of airspace disease (AD) derived from a superior modality (computed tomogr...

Extracting postmarketing adverse events from safety reports in the vaccine adverse event reporting system (VAERS) using deep learning.

OBJECTIVE: Automated analysis of vaccine postmarketing surveillance narrative reports is important to understand the progression of rare but severe va...

Creative Approaches for Assessing Long-term Outcomes in Children.

Advances in new technologies, when incorporated into routine health screening, have tremendous promise to benefit children. The number of health scree...