AIMC Topic: Disease Transmission, Infectious
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IDNetwork: A deep illness-death network based on multi-state event history process for disease prognostication.
Statistics in medicine
Feb 17, 2022
Multi-state models can capture the different patterns of disease evolution. In particular, the illness-death model is used to follow disease progression from a healthy state to an intermediate state of the disease and to a death-related final state. ...
Application of artificial neural networks to predict the COVID-19 outbreak.
Global health research and policy
Nov 23, 2020
BACKGROUND: Millions of people have been infected worldwide in the COVID-19 pandemic. In this study, we aim to propose fourteen prediction models based on artificial neural networks (ANN) to predict the COVID-19 outbreak for policy makers.
Advances in Telemedicine in Ophthalmology.
Seminars in ophthalmology
Jul 9, 2020
Telemedicine is the provision of healthcare-related services from a distance and is poised to move healthcare from the physician's office back into the patient's home. The field of ophthalmology is often at the forefront of technological advances in ...
Classification and Morphological Analysis of Vector Mosquitoes using Deep Convolutional Neural Networks.
Scientific reports
Jan 23, 2020
Image-based automatic classification of vector mosquitoes has been investigated for decades for its practical applications such as early detection of potential mosquitoes-borne diseases. However, the classification accuracy of previous approaches has...
Biocontrol potential of Halotolerant bacterial chitinase from high yielding novel Bacillus Pumilus MCB-7 autochthonous to mangrove ecosystem.
Pesticide biochemistry and physiology
Sep 28, 2016
The multifaceted role of chitinase in medicine, agriculture, environmental remediation and various other industries greatly demands the isolation of high yielding chitinase producing microorganisms with improved properties. The current study aimed to...
Network context matters: graph convolutional network model over social networks improves the detection of unknown HIV infections among young men who have sex with men.
Journal of the American Medical Informatics Association : JAMIA
Nov 1, 2019
OBJECTIVE: HIV infection risk can be estimated based on not only individual features but also social network information. However, there have been insufficient studies using n machine learning methods that can maximize the utility of such information...
Near Full-length Genomic Sequencing and Molecular Analysis of HIV-Infected Individuals in a Network-based Intervention (TRIP) in Athens, Greece: Evidence that Transmissions Occur More Frequently from those with High HIV-RNA.
Current HIV research
Jan 1, 2018
BACKGROUND: TRIP (Transmission Reduction Intervention Project) was a network-based, contact tracing approach to locate and link to care, mostly people who inject drugs (PWID) with recent HIV infection.
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