AI Medical Compendium Topic:
COVID-19

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Association between loneliness and acceptance of using robots and pets as companions among older Chinese immigrants during the COVID-19 pandemic.

Australasian journal on ageing
OBJECTIVES: To examine loneliness experienced by middle-aged and older Chinese immigrants and its association with accepting technology as a companion (apps, Internet and robots) versus owning pets, when social distancing measures were implemented in...

An original deep learning model using limited data for COVID-19 discrimination: A multicenter study.

Medical physics
OBJECTIVES: Artificial intelligence (AI) has been proved to be a highly efficient tool for COVID-19 diagnosis, but the large data size and heavy label force required for algorithm development and the poor generalizability of AI algorithms, to some ex...

TSRNet: Diagnosis of COVID-19 based on self-supervised learning and hybrid ensemble model.

Computers in biology and medicine
BACKGROUND: As of Feb 27, 2022, coronavirus (COVID-19) has caused 434,888,591 infections and 5,958,849 deaths worldwide, dealing a severe blow to the economies and cultures of most countries around the world. As the virus has mutated, its infectious ...

Proposing Causal Sequence of Death by Neural Machine Translation in Public Health Informatics.

IEEE journal of biomedical and health informatics
Each year there are nearly 57 million deaths worldwide, with over 2.7 million in the United States. Timely, accurate and complete death reporting is critical for public health, especially during the COVID-19 pandemic, as institutions and government a...

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

IEEE journal of biomedical and health informatics
Deep learning based methods have shown great promise in achieving accurate automatic detection of Coronavirus Disease (covid) - 19 from Chest X-Ray (cxr) images.However, incorporating explainability in these solutions remains relatively less explored...

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

Scientific reports
The COVID-19 pandemic repeatedly overwhelms healthcare systems capacity and forced the development and implementation of triage guidelines in ICU for scarce resources (e.g. mechanical ventilation). These guidelines were often based on known risk fact...

Diagnosis of Lumbar Spondylolisthesis Using Optimized Pretrained CNN Models.

Computational intelligence and neuroscience
Spondylolisthesis refers to the slippage of one vertebral body over the adjacent one. It is a chronic condition that requires early detection to prevent unpleasant surgery. The paper presents an optimized deep learning model for detecting spondylolis...

Detection of COVID-19 from CT and Chest X-ray Images Using Deep Learning Models.

Annals of biomedical engineering
Coronavirus 2019 (COVID-19) is a highly transmissible and pathogenic virus caused by severe respiratory syndrome coronavirus 2 (SARS-CoV-2), which first appeared in Wuhan, China, and has since spread in the whole world. This pathology has caused a ma...

COV-DLS: Prediction of COVID-19 from X-Rays Using Enhanced Deep Transfer Learning Techniques.

Journal of healthcare engineering
In this paper, modifications in neoteric architectures such as VGG16, VGG19, ResNet50, and InceptionV3 are proposed for the classification of COVID-19 using chest X-rays. The proposed architectures termed "COV-DLS" consist of two phases: heading mode...

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

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