Publications des scientifiques de l'IRD

Ezanno P., Picault S., Beaunee G., Bailly X., Munoz F., Duboz R., Monod H., Guégan Jean-François. (2021). Research perspectives on animal health in the era of artificial intelligence. Veterinary Research, 52 (1), p. 40 [15 p.]. ISSN 0928-4249.

Titre du document
Research perspectives on animal health in the era of artificial intelligence
Année de publication
2021
Type de document
Article référencé dans le Web of Science WOS:000626557100001
Auteurs
Ezanno P., Picault S., Beaunee G., Bailly X., Munoz F., Duboz R., Monod H., Guégan Jean-François
Source
Veterinary Research, 2021, 52 (1), p. 40 [15 p.] ISSN 0928-4249
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 hostxpathogen 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.
Plan de classement
Sciences fondamentales / Techniques d'analyse et de recherche [020] ; Sciences du monde animal [080] ; Informatique [122]
Localisation
Fonds IRD [F B010081100]
Identifiant IRD
fdi:010081100
Contact