AIMC Topic: COVID-19

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Graphic Model of Virtual Teaching Supervision through Fuzzy Logic in Non-University Educational Centers.

International journal of environmental research and public health
This research analyzes the supervision of non-university virtual training due to the unexpected non-face-to-face teaching scenario caused by COVID-19 with a graphic model using the SULODITOOL instrument. It arises as a research line of the Chair of E...

Image Translation by Ad CycleGAN for COVID-19 X-Ray Images: A New Approach for Controllable GAN.

Sensors (Basel, Switzerland)
We propose a new generative model named adaptive cycle-consistent generative adversarial network, or Ad CycleGAN to perform image translation between normal and COVID-19 positive chest X-ray images. An independent pre-trained criterion is added to th...

Semantic-Powered Explainable Model-Free Few-Shot Learning Scheme of Diagnosing COVID-19 on Chest X-Ray.

IEEE journal of biomedical and health informatics
Chest X-ray (CXR) is commonly performed as an initial investigation in COVID-19, whose fast and accurate diagnosis is critical. Recently, deep learning has a great potential in detecting people who are suspected to be infected with COVID-19. However,...

Considerations and Challenges for Real-World Deployment of an Acoustic-Based COVID-19 Screening System.

Sensors (Basel, Switzerland)
Coronavirus disease 2019 (COVID-19) has led to countless deaths and widespread global disruptions. Acoustic-based artificial intelligence (AI) tools could provide a simple, scalable, and prompt method to screen for COVID-19 using easily acquirable ph...

Deep Learning of Dual Plasma Fingerprints for High-Performance Infection Classification.

Small (Weinheim an der Bergstrasse, Germany)
Infection classification is the key for choosing the proper treatment plans. Early determination of the causative agents is critical for disease control. Host responses analysis can detect variform and sensitive host inflammatory responses to ascerta...

Analyzing factors contributing to COVID-19 mortality in the United States using artificial intelligence techniques.

Risk analysis : an official publication of the Society for Risk Analysis
Having started since late 2019, COVID-19 has spread through far many nations around the globe. Not being known profoundly, the novel virus of the Coronaviruses family has already caused more than half a million deaths and put the lives of many more p...

Year 2021: COVID-19, Information Extraction and BERTization among the Hottest Topics in Medical Natural Language Processing.

Yearbook of medical informatics
OBJECTIVES: Analyze the content of publications within the medical natural language processing (NLP) domain in 2021.

Characterizing Macrophages Diversity in COVID-19 Patients Using Deep Learning.

Genes
The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the etiological agent responsible for coronavirus disease 2019 (COVID-19), has affected the lives of billions and killed millions of infected people. This virus has been demonstrated t...

3D CT-Inclusive Deep-Learning Model to Predict Mortality, ICU Admittance, and Intubation in COVID-19 Patients.

Journal of digital imaging
Chest CT is a useful initial exam in patients with coronavirus disease 2019 (COVID-19) for assessing lung damage. AI-powered predictive models could be useful to better allocate resources in the midst of the pandemic. Our aim was to build a deep-lear...

Off the deep end: What can deep learning do for the gene expression field?

The Journal of biological chemistry
After a COVID-related hiatus, the fifth biennial symposium on Evolution and Core Processes in Gene Regulation met at the Stowers Institute in Kansas City, Missouri July 21 to 24, 2022. This symposium, sponsored by the American Society for Biochemistr...