AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Pneumonia, Viral

Showing 221 to 230 of 277 articles

Clear Filters

DDA-SSNets: Dual decoder attention-based semantic segmentation networks for COVID-19 infection segmentation and classification using chest X-Ray images.

Journal of X-ray science and technology
BACKGROUND: COVID-19 needs to be diagnosed and staged to be treated accurately. However, prior studies' diagnostic and staging abilities for COVID-19 infection needed to be improved. Therefore, new deep learning-based approaches are required to aid r...

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

Journal of X-ray science and technology
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 using PCR Swab method. However, accuracy of using X-ray images needs to be improved.

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

Journal of X-ray science and technology
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. Examinations also found that even if the COVID-19 patients initially survived the coronavirus, pneumon...

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

Iranian journal of medical sciences
BACKGROUND: Chest computed tomography (CT) plays an essential role in diagnosing coronavirus disease 2019 (COVID-19). However, CT findings are often nonspecific among different viral pneumonia conditions. The differentiation between COVID-19 and infl...

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

Medicine
Coronavirus disease (COVID-19) has spread worldwide. X-ray and computed tomography (CT) are 2 technologies widely used in image acquisition, segmentation, diagnosis, and evaluation. Artificial intelligence can accurately segment infected parts in X-r...

FLANNEL (Focal Loss bAsed Neural Network EnsembLe) for COVID-19 detection.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: The study sought to test the possibility of differentiating chest x-ray images of coronavirus disease 2019 (COVID-19) against other pneumonia and healthy patients using deep neural networks.

Retrospective analysis of the accuracy of predicting the alert level of COVID-19 in 202 countries using Google Trends and machine learning.

Journal of global health
BACKGROUND: Internet search engine data, such as Google Trends, was shown to be correlated with the incidence of COVID-19, but only in several countries. We aim to develop a model from a small number of countries to predict the epidemic alert level i...

Latent COVID-19 Clusters in Patients with Chronic Respiratory Conditions.

Studies in health technology and informatics
The goal of this paper was to apply unsupervised machine learning techniques towards the discovery of latent COVID-19 clusters in patients with chronic lower respiratory diseases (CLRD). Patients who underwent testing for SARS-CoV-2 were identified f...

Deep learning applications to combat the dissemination of COVID-19 disease: a review.

European review for medical and pharmacological sciences
Recent Coronavirus (COVID-19) is one of the respiratory diseases, and it is known as fast infectious ability. This dissemination can be decelerated by diagnosing and quarantining patients with COVID-19 at early stages, thereby saving numerous lives. ...