AIMC Topic: SARS-CoV-2

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Standard for the Quantification of a Sterilization Effect Using an Artificial Intelligence Disinfection Robot.

Sensors (Basel, Switzerland)
Recent outbreaks and the worldwide spread of COVID-19 have challenged mankind with unprecedented difficulties. The introduction of autonomous disinfection robots appears to be indispensable as consistent sterilization is in desperate demand under lim...

Improving patient flow during infectious disease outbreaks using machine learning for real-time prediction of patient readiness for discharge.

PloS one
BACKGROUND: Delays in patient flow and a shortage of hospital beds are commonplace in hospitals during periods of increased infection incidence, such as seasonal influenza and the COVID-19 pandemic. The objective of this study was to develop and eval...

UMLF-COVID: an unsupervised meta-learning model specifically designed to identify X-ray images of COVID-19 patients.

BMC medical imaging
BACKGROUND: With the rapid spread of COVID-19 worldwide, quick screening for possible COVID-19 patients has become the focus of international researchers. Recently, many deep learning-based Computed Tomography (CT) image/X-ray image fast screening mo...

Combined deep learning and molecular docking simulations approach identifies potentially effective FDA approved drugs for repurposing against SARS-CoV-2.

Computers in biology and medicine
The ongoing pandemic of Coronavirus Disease 2019 (COVID-19) has posed a serious threat to global public health. Drug repurposing is a time-efficient approach to finding effective drugs against SARS-CoV-2 in this emergency. Here, we present a robust e...

A Hybrid Convolutional Neural Network Model for Diagnosis of COVID-19 Using Chest X-ray Images.

International journal of environmental research and public health
COVID-19 declared as a pandemic that has a faster rate of infection and has impacted the lives and the country's economy due to forced lockdowns. Its detection using RT-PCR is required long time and due to which its infection has grown exponentially....

Numerical Investigations through ANNs for Solving COVID-19 Model.

International journal of environmental research and public health
The current investigations of the COVID-19 spreading model are presented through the artificial neuron networks (ANNs) with training of the Levenberg-Marquardt backpropagation (LMB), i.e., ANNs-LMB. The ANNs-LMB scheme is used in different variations...

Mix Contrast for COVID-19 Mild-to-Critical Prediction.

IEEE transactions on bio-medical engineering
OBJECTIVE: In a few patients with mild COVID-19, there is a possibility of the infection becoming severe or critical in the future. This work aims to identify high-risk patients who have a high probability of changing from mild to critical COVID-19 (...

Natural language processing and network analysis provide novel insights on policy and scientific discourse around Sustainable Development Goals.

Scientific reports
The United Nations' (UN) Sustainable Development Goals (SDGs) are heterogeneous and interdependent, comprising 169 targets and 231 indicators of sustainable development in such diverse areas as health, the environment, and human rights. Existing effo...

Artificial intelligence for imaging-based COVID-19 detection: Systematic review comparing added value of AI versus human readers.

European journal of radiology
PURPOSE: A growing number of studies have examined whether Artificial Intelligence (AI) systems can support imaging-based diagnosis of COVID-19-caused pneumonia, including both gains in diagnostic performance and speed. However, what is currently mis...

Potential diagnosis of COVID-19 from chest X-ray and CT findings using semi-supervised learning.

Physical and engineering sciences in medicine
COVID-19 is an infectious disease, which has adversely affected public health and the economy across the world. On account of the highly infectious nature of the disease, rapid automated diagnosis of COVID-19 is urgently needed. A few recent findings...