AIMC Topic: SARS-CoV-2

Clear Filters Showing 1031 to 1040 of 1734 articles

Contrasting factors associated with COVID-19-related ICU admission and death outcomes in hospitalised patients by means of Shapley values.

PLoS computational biology
Identification of those at greatest risk of death due to the substantial threat of COVID-19 can benefit from novel approaches to epidemiology that leverage large datasets and complex machine-learning models, provide data-driven intelligence, and guid...

COVID-19 deep classification network based on convolution and deconvolution local enhancement.

Computers in biology and medicine
Computer Tomography (CT) detection can effectively overcome the problems of traditional detection of Corona Virus Disease 2019 (COVID-19), such as lagging detection results and wrong diagnosis results, which lead to the increase of disease infection ...

On-Site Detection of SARS-CoV-2 Antigen by Deep Learning-Based Surface-Enhanced Raman Spectroscopy and Its Biochemical Foundations.

Analytical chemistry
A rapid, on-site, and accurate SARS-CoV-2 detection method is crucial for the prevention and control of the COVID-19 epidemic. However, such an ideal screening technology has not yet been developed for the diagnosis of SARS-CoV-2. Here, we have devel...

Deep Learning-Based Stroke Disease Prediction System Using Real-Time Bio Signals.

Sensors (Basel, Switzerland)
The emergence of an aging society is inevitable due to the continued increases in life expectancy and decreases in birth rate. These social changes require new smart healthcare services for use in daily life, and COVID-19 has also led to a contactles...

Folding non-homologous proteins by coupling deep-learning contact maps with I-TASSER assembly simulations.

Cell reports methods
Structure prediction for proteins lacking homologous templates in the Protein Data Bank (PDB) remains a significant unsolved problem. We developed a protocol, C-I-TASSER, to integrate interresidue contact maps from deep neural-network learning with t...

Detecting COVID-19 in Chest X-Ray Images via MCFF-Net.

Computational intelligence and neuroscience
COVID-19 is a respiratory disease caused by severe acute respiratory syndrome coronavirus (SARS-CoV-2). Due to the rapid spread of COVID-19 around the world, the number of COVID-19 cases continues to increase, and lots of countries are facing tremend...

Multivariable mortality risk prediction using machine learning for COVID-19 patients at admission (AICOVID).

Scientific reports
In Coronavirus disease 2019 (COVID-19), early identification of patients with a high risk of mortality can significantly improve triage, bed allocation, timely management, and possibly, outcome. The study objective is to develop and validate individu...

Combining machine learning and nanopore construction creates an artificial intelligence nanopore for coronavirus detection.

Nature communications
High-throughput, high-accuracy detection of emerging viruses allows for the control of disease outbreaks. Currently, reverse transcription-polymerase chain reaction (RT-PCR) is currently the most-widely used technology to diagnose the presence of SAR...

Deep convolutional neural networks for COVID-19 automatic diagnosis.

Microscopy research and technique
This article is mainly concerned with COVID-19 diagnosis from X-ray images. The number of cases infected with COVID-19 is increasing daily, and there is a limitation in the number of test kits needed in hospitals. Therefore, there is an imperative ne...