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Artificial Intelligence Models for Zoonotic Pathogens: A Survey

Zoonotic diseases or zoonoses are infections due to the natural transmission of pathogens between species (animals and humans). More than 70% of emerging infectious diseases are attributed to animal origin. Artificial Intelligence (AI) models have been used for studying zoonotic pathogens and the fa...

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Autores principales: Pillai, Nisha, Ramkumar, Mahalingam, Nanduri, Bindu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9607465/
https://www.ncbi.nlm.nih.gov/pubmed/36296187
http://dx.doi.org/10.3390/microorganisms10101911
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author Pillai, Nisha
Ramkumar, Mahalingam
Nanduri, Bindu
author_facet Pillai, Nisha
Ramkumar, Mahalingam
Nanduri, Bindu
author_sort Pillai, Nisha
collection PubMed
description Zoonotic diseases or zoonoses are infections due to the natural transmission of pathogens between species (animals and humans). More than 70% of emerging infectious diseases are attributed to animal origin. Artificial Intelligence (AI) models have been used for studying zoonotic pathogens and the factors that contribute to their spread. The aim of this literature survey is to synthesize and analyze machine learning, and deep learning approaches applied to study zoonotic diseases to understand predictive models to help researchers identify the risk factors, and develop mitigation strategies. Based on our survey findings, machine learning and deep learning are commonly used for the prediction of both foodborne and zoonotic pathogens as well as the factors associated with the presence of the pathogens.
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spelling pubmed-96074652022-10-28 Artificial Intelligence Models for Zoonotic Pathogens: A Survey Pillai, Nisha Ramkumar, Mahalingam Nanduri, Bindu Microorganisms Review Zoonotic diseases or zoonoses are infections due to the natural transmission of pathogens between species (animals and humans). More than 70% of emerging infectious diseases are attributed to animal origin. Artificial Intelligence (AI) models have been used for studying zoonotic pathogens and the factors that contribute to their spread. The aim of this literature survey is to synthesize and analyze machine learning, and deep learning approaches applied to study zoonotic diseases to understand predictive models to help researchers identify the risk factors, and develop mitigation strategies. Based on our survey findings, machine learning and deep learning are commonly used for the prediction of both foodborne and zoonotic pathogens as well as the factors associated with the presence of the pathogens. MDPI 2022-09-27 /pmc/articles/PMC9607465/ /pubmed/36296187 http://dx.doi.org/10.3390/microorganisms10101911 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Review
Pillai, Nisha
Ramkumar, Mahalingam
Nanduri, Bindu
Artificial Intelligence Models for Zoonotic Pathogens: A Survey
title Artificial Intelligence Models for Zoonotic Pathogens: A Survey
title_full Artificial Intelligence Models for Zoonotic Pathogens: A Survey
title_fullStr Artificial Intelligence Models for Zoonotic Pathogens: A Survey
title_full_unstemmed Artificial Intelligence Models for Zoonotic Pathogens: A Survey
title_short Artificial Intelligence Models for Zoonotic Pathogens: A Survey
title_sort artificial intelligence models for zoonotic pathogens: a survey
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9607465/
https://www.ncbi.nlm.nih.gov/pubmed/36296187
http://dx.doi.org/10.3390/microorganisms10101911
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