AIMC Topic: SARS-CoV-2

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A deep learning approach using effective preprocessing techniques to detect COVID-19 from chest CT-scan and X-ray images.

Computers in biology and medicine
Coronavirus disease-19 (COVID-19) is a severe respiratory viral disease first reported in late 2019 that has spread worldwide. Although some wealthy countries have made significant progress in detecting and containing this disease, most underdevelope...

EpistoNet: an ensemble of Epistocracy-optimized mixture of experts for detecting COVID-19 on chest X-ray images.

Scientific reports
The Coronavirus has spread across the world and infected millions of people, causing devastating damage to the public health and global economies. To mitigate the impact of the coronavirus a reliable, fast, and accurate diagnostic system should be pr...

COVID-19 Case Recognition from Chest CT Images by Deep Learning, Entropy-Controlled Firefly Optimization, and Parallel Feature Fusion.

Sensors (Basel, Switzerland)
In healthcare, a multitude of data is collected from medical sensors and devices, such as X-ray machines, magnetic resonance imaging, computed tomography (CT), and so on, that can be analyzed by artificial intelligence methods for early diagnosis of ...

HoloMentor: A Novel Mixed Reality Surgical Anatomy Curriculum for Robot-Assisted Radical Prostatectomy.

European surgical research. Europaische chirurgische Forschung. Recherches chirurgicales europeennes
OBJECTIVES: The disruption to surgical training and medical education caused by the global COVID-19 pandemic highlighted the need for realistic, reliable, and engaging educational opportunities available outside of the operating theatre and accessibl...

A novel deep neuroevolution-based image classification method to diagnose coronavirus disease (COVID-19).

Computers in biology and medicine
COVID-19 has had a detrimental impact on normal activities, public safety, and the global financial system. To identify the presence of this disease within communities and to commence the management of infected patients early, positive cases should b...

Estimating the COVID-19 prevalence and mortality using a novel data-driven hybrid model based on ensemble empirical mode decomposition.

Scientific reports
In this study, we proposed a new data-driven hybrid technique by integrating an ensemble empirical mode decomposition (EEMD), an autoregressive integrated moving average (ARIMA), with a nonlinear autoregressive artificial neural network (NARANN), cal...

Deep Learning-Based Methods for Sentiment Analysis on Nepali COVID-19-Related Tweets.

Computational intelligence and neuroscience
COVID-19 has claimed several human lives to this date. People are dying not only because of physical infection of the virus but also because of mental illness, which is linked to people's sentiments and psychologies. People's written texts/posts scat...

Automated Processing and Phenotype Extraction of Ovine Medical Images Using a Combined Generative Adversarial Network and Computer Vision Pipeline.

Sensors (Basel, Switzerland)
The speed and accuracy of phenotype detection from medical images are some of the most important qualities needed for any informed and timely response such as early detection of cancer or detection of desirable phenotypes for animal breeding. To impr...

Role of Digital Health During Coronavirus Disease 2019 Pandemic and Future Perspectives.

Cardiac electrophysiology clinics
Coronavirus disease 2019 revolutionized the digital health care. This pandemic was the catalyst for not only a sudden but also widespread paradigm shift in patient care, with nearly 80% of the US population indicating that they have used one form of ...