AIMC Topic: COVID-19

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COVIDSAVIOR: A Novel Sensor-Fusion and Deep Learning Based Framework for Virus Outbreaks.

Frontiers in public health
The presented deep learning and sensor-fusion based assistive technology (Smart Facemask and Thermal scanning kiosk) will protect the individual using auto face-mask detection and auto thermal scanning to detect the current body temperature. Furtherm...

Short- and Long-Term Recovery after Moderate/Severe AKI in Patients with and without COVID-19.

Kidney360
BACKGROUND: Severe AKI is strongly associated with poor outcomes in coronavirus disease 2019 (COVID-19), but data on renal recovery are lacking.

Mild Adverse Events of Sputnik V Vaccine in Russia: Social Media Content Analysis of Telegram via Deep Learning.

Journal of medical Internet research
BACKGROUND: There is a limited amount of data on the safety profile of the COVID-19 vector vaccine Gam-COVID-Vac (Sputnik V). Previous infodemiology studies showed that social media discourse could be analyzed to assess the most concerning adverse ev...

Machine Learning-based Voice Assessment for the Detection of Positive and Recovered COVID-19 Patients.

Journal of voice : official journal of the Voice Foundation
Many virological tests have been implemented during the Coronavirus Disease 2019 (COVID-19) pandemic for diagnostic purposes, but they appear unsuitable for screening purposes. Furthermore, current screening strategies are not accurate enough to effe...

Using explainable machine learning to characterise data drift and detect emergent health risks for emergency department admissions during COVID-19.

Scientific reports
A key task of emergency departments is to promptly identify patients who require hospital admission. Early identification ensures patient safety and aids organisational planning. Supervised machine learning algorithms can use data describing historic...

A Novel and Robust Approach to Detect Tuberculosis Using Transfer Learning.

Journal of healthcare engineering
Deep learning has emerged as a promising technique for a variety of elements of infectious disease monitoring and detection, including . We built a deep convolutional neural network (CNN) model to assess the generalizability of the deep learning mode...

Trends in the application of deep learning networks in medical image analysis: Evolution between 2012 and 2020.

European journal of radiology
PURPOSE: To evaluate the general rules and future trajectories of deep learning (DL) networks in medical image analysis through bibliometric and hot spot analysis of original articles published between 2012 and 2020.

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...