Research perspectives on animal health in the era of artificial intelligence

Leveraging artificial intelligence (AI) approaches in animal health (AH) makes it possible to address highly complex issues such as those encountered in quantitative and predictive epidemiology, animal/human precision-based medicine, or to study host × pathogen interactions. AI may contribute (i) to diagnosis and disease case detection, (ii) to more reliable predictions and reduced errors, (iii) to representing more realistically complex biological systems and rendering computing codes more readable to non-computer scientists, (iv) to speeding-up decisions and improving accuracy in risk analyses, and (v) to better targeted interventions and anticipated negative effects. In turn, challenges in AH may stimulate AI research due to specificity of AH systems, data, constraints, and analytical objectives. Based on a literature review of scientific papers at the interface between AI and AH covering the period 2009–2019, and interviews with French researchers positioned at this interface, the present study explains the main AH areas where various AI approaches are currently mobilised, how it may contribute to renew AH research issues and remove methodological or conceptual barriers. After presenting the possible obstacles and levers, we propose several recommendations to better grasp the challenge represented by the AH/AI interface. With the development of several recent concepts promoting a global and multisectoral perspective in the field of health, AI should contribute to defract the different disciplines in AH towards more transversal and integrative research.

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Main Authors: Ezanno, Pauline, Picault, Sébastien, Beaunée, Gaël, Bailly, Xavier, Munoz, Facundo, Duboz, Raphaël, Monod, Hervé, Guégan, Jean-François
Format: article biblioteca
Language:eng
Subjects:L73 - Maladies des animaux, maladie des animaux, santé animale, intelligence artificielle, modélisation, système d'aide à la décision, épidémiologie, http://aims.fao.org/aos/agrovoc/c_426, http://aims.fao.org/aos/agrovoc/c_431, http://aims.fao.org/aos/agrovoc/c_27064, http://aims.fao.org/aos/agrovoc/c_230ab86c, http://aims.fao.org/aos/agrovoc/c_49868, http://aims.fao.org/aos/agrovoc/c_2615,
Online Access:http://agritrop.cirad.fr/597870/
http://agritrop.cirad.fr/597870/1/Ezanno%20et%20al.%20-%202021%20-%20Research%20perspectives%20on%20animal%20health%20in%20the%20era%20.pdf
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spelling dig-cirad-fr-5978702024-01-29T03:25:13Z http://agritrop.cirad.fr/597870/ http://agritrop.cirad.fr/597870/ Research perspectives on animal health in the era of artificial intelligence. Ezanno Pauline, Picault Sébastien, Beaunée Gaël, Bailly Xavier, Munoz Facundo, Duboz Raphaël, Monod Hervé, Guégan Jean-François. 2021. Veterinary Research, 52:40, 15 p.https://doi.org/10.1186/s13567-021-00902-4 <https://doi.org/10.1186/s13567-021-00902-4> Research perspectives on animal health in the era of artificial intelligence Ezanno, Pauline Picault, Sébastien Beaunée, Gaël Bailly, Xavier Munoz, Facundo Duboz, Raphaël Monod, Hervé Guégan, Jean-François eng 2021 Veterinary Research L73 - Maladies des animaux maladie des animaux santé animale intelligence artificielle modélisation système d'aide à la décision épidémiologie http://aims.fao.org/aos/agrovoc/c_426 http://aims.fao.org/aos/agrovoc/c_431 http://aims.fao.org/aos/agrovoc/c_27064 http://aims.fao.org/aos/agrovoc/c_230ab86c http://aims.fao.org/aos/agrovoc/c_49868 http://aims.fao.org/aos/agrovoc/c_2615 Leveraging artificial intelligence (AI) approaches in animal health (AH) makes it possible to address highly complex issues such as those encountered in quantitative and predictive epidemiology, animal/human precision-based medicine, or to study host × pathogen interactions. AI may contribute (i) to diagnosis and disease case detection, (ii) to more reliable predictions and reduced errors, (iii) to representing more realistically complex biological systems and rendering computing codes more readable to non-computer scientists, (iv) to speeding-up decisions and improving accuracy in risk analyses, and (v) to better targeted interventions and anticipated negative effects. In turn, challenges in AH may stimulate AI research due to specificity of AH systems, data, constraints, and analytical objectives. Based on a literature review of scientific papers at the interface between AI and AH covering the period 2009–2019, and interviews with French researchers positioned at this interface, the present study explains the main AH areas where various AI approaches are currently mobilised, how it may contribute to renew AH research issues and remove methodological or conceptual barriers. After presenting the possible obstacles and levers, we propose several recommendations to better grasp the challenge represented by the AH/AI interface. With the development of several recent concepts promoting a global and multisectoral perspective in the field of health, AI should contribute to defract the different disciplines in AH towards more transversal and integrative research. article info:eu-repo/semantics/article Journal Article info:eu-repo/semantics/publishedVersion http://agritrop.cirad.fr/597870/1/Ezanno%20et%20al.%20-%202021%20-%20Research%20perspectives%20on%20animal%20health%20in%20the%20era%20.pdf text cc_by info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by/4.0/ https://doi.org/10.1186/s13567-021-00902-4 10.1186/s13567-021-00902-4 info:eu-repo/semantics/altIdentifier/doi/10.1186/s13567-021-00902-4 info:eu-repo/semantics/altIdentifier/purl/https://doi.org/10.1186/s13567-021-00902-4 info:eu-repo/grantAgreement/EC/H2020/874850//(EU) MOnitoring Outbreak events for Disease surveillance in a data science context/MOOD
institution CIRAD FR
collection DSpace
country Francia
countrycode FR
component Bibliográfico
access En linea
databasecode dig-cirad-fr
tag biblioteca
region Europa del Oeste
libraryname Biblioteca del CIRAD Francia
language eng
topic L73 - Maladies des animaux
maladie des animaux
santé animale
intelligence artificielle
modélisation
système d'aide à la décision
épidémiologie
http://aims.fao.org/aos/agrovoc/c_426
http://aims.fao.org/aos/agrovoc/c_431
http://aims.fao.org/aos/agrovoc/c_27064
http://aims.fao.org/aos/agrovoc/c_230ab86c
http://aims.fao.org/aos/agrovoc/c_49868
http://aims.fao.org/aos/agrovoc/c_2615
L73 - Maladies des animaux
maladie des animaux
santé animale
intelligence artificielle
modélisation
système d'aide à la décision
épidémiologie
http://aims.fao.org/aos/agrovoc/c_426
http://aims.fao.org/aos/agrovoc/c_431
http://aims.fao.org/aos/agrovoc/c_27064
http://aims.fao.org/aos/agrovoc/c_230ab86c
http://aims.fao.org/aos/agrovoc/c_49868
http://aims.fao.org/aos/agrovoc/c_2615
spellingShingle L73 - Maladies des animaux
maladie des animaux
santé animale
intelligence artificielle
modélisation
système d'aide à la décision
épidémiologie
http://aims.fao.org/aos/agrovoc/c_426
http://aims.fao.org/aos/agrovoc/c_431
http://aims.fao.org/aos/agrovoc/c_27064
http://aims.fao.org/aos/agrovoc/c_230ab86c
http://aims.fao.org/aos/agrovoc/c_49868
http://aims.fao.org/aos/agrovoc/c_2615
L73 - Maladies des animaux
maladie des animaux
santé animale
intelligence artificielle
modélisation
système d'aide à la décision
épidémiologie
http://aims.fao.org/aos/agrovoc/c_426
http://aims.fao.org/aos/agrovoc/c_431
http://aims.fao.org/aos/agrovoc/c_27064
http://aims.fao.org/aos/agrovoc/c_230ab86c
http://aims.fao.org/aos/agrovoc/c_49868
http://aims.fao.org/aos/agrovoc/c_2615
Ezanno, Pauline
Picault, Sébastien
Beaunée, Gaël
Bailly, Xavier
Munoz, Facundo
Duboz, Raphaël
Monod, Hervé
Guégan, Jean-François
Research perspectives on animal health in the era of artificial intelligence
description Leveraging artificial intelligence (AI) approaches in animal health (AH) makes it possible to address highly complex issues such as those encountered in quantitative and predictive epidemiology, animal/human precision-based medicine, or to study host × pathogen interactions. AI may contribute (i) to diagnosis and disease case detection, (ii) to more reliable predictions and reduced errors, (iii) to representing more realistically complex biological systems and rendering computing codes more readable to non-computer scientists, (iv) to speeding-up decisions and improving accuracy in risk analyses, and (v) to better targeted interventions and anticipated negative effects. In turn, challenges in AH may stimulate AI research due to specificity of AH systems, data, constraints, and analytical objectives. Based on a literature review of scientific papers at the interface between AI and AH covering the period 2009–2019, and interviews with French researchers positioned at this interface, the present study explains the main AH areas where various AI approaches are currently mobilised, how it may contribute to renew AH research issues and remove methodological or conceptual barriers. After presenting the possible obstacles and levers, we propose several recommendations to better grasp the challenge represented by the AH/AI interface. With the development of several recent concepts promoting a global and multisectoral perspective in the field of health, AI should contribute to defract the different disciplines in AH towards more transversal and integrative research.
format article
topic_facet L73 - Maladies des animaux
maladie des animaux
santé animale
intelligence artificielle
modélisation
système d'aide à la décision
épidémiologie
http://aims.fao.org/aos/agrovoc/c_426
http://aims.fao.org/aos/agrovoc/c_431
http://aims.fao.org/aos/agrovoc/c_27064
http://aims.fao.org/aos/agrovoc/c_230ab86c
http://aims.fao.org/aos/agrovoc/c_49868
http://aims.fao.org/aos/agrovoc/c_2615
author Ezanno, Pauline
Picault, Sébastien
Beaunée, Gaël
Bailly, Xavier
Munoz, Facundo
Duboz, Raphaël
Monod, Hervé
Guégan, Jean-François
author_facet Ezanno, Pauline
Picault, Sébastien
Beaunée, Gaël
Bailly, Xavier
Munoz, Facundo
Duboz, Raphaël
Monod, Hervé
Guégan, Jean-François
author_sort Ezanno, Pauline
title Research perspectives on animal health in the era of artificial intelligence
title_short Research perspectives on animal health in the era of artificial intelligence
title_full Research perspectives on animal health in the era of artificial intelligence
title_fullStr Research perspectives on animal health in the era of artificial intelligence
title_full_unstemmed Research perspectives on animal health in the era of artificial intelligence
title_sort research perspectives on animal health in the era of artificial intelligence
url http://agritrop.cirad.fr/597870/
http://agritrop.cirad.fr/597870/1/Ezanno%20et%20al.%20-%202021%20-%20Research%20perspectives%20on%20animal%20health%20in%20the%20era%20.pdf
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