Korean Journal of Veterinary Service (한국동물위생학회지)

The Korean Society of Veterinary Service (한국동물위생학회)
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Bibliographic and network analysis of environmental impacts to animal contagious diseases

  • Jee-Sun, Oh (School of Business and Technology Management, Korea Advanced Institute of Science and Technology) ;
  • Sang-Joon, Lee (College of Veterinary Medicine and Institute of Veterinary Science, Kangwon National University) ;
  • Sang Jin, Lim (College of Forest & Environmental Sciences and Institute of Forest Science, Kangwon National University) ;
  • Yung Chul, Park (College of Forest & Environmental Sciences and Institute of Forest Science, Kangwon National University) ;
  • Ho-Seong, Cho (College of Veterinary Medicine and Bio-safety Research Institute, Jeonbuk National University) ;
  • Yeonsu, Oh (College of Veterinary Medicine and Institute of Veterinary Science, Kangwon National University)
  • Received : 2022.09.09
  • Accepted : 2022.12.01
  • Published : 2022.12.30
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Abstract

The applications of artificial intelligence (AI) can provide useful solutions to animal infectious diseases and their impact on humans. The advent of AI learning algorithms and recognition technologies is especially advantageous in applied studies, including the detection, analysis, impact assessment, simulation, and prediction of environmental impacts on malignant animal epidemics. To this end, this study specifically focused on environmental pollution and animal diseases. While the number of related studies is rapidly increasing, the research trends, evolution, and collaboration in this field are not yet well-established. We analyzed the bibliographic data of 1191 articles on AI applications to environmental pollution and animal diseases during the period of 2000~2019; these articles were collected from the Web of Science (WoS). The results revealed that PR China and the United States are the leaders in research production, impact, and collaboration. Finally, we provided research directions and practical implications for the incorporation of AI applications to address environmental impacts on animal diseases.

Keywords

Acknowledgement

This work was supported by the Korea Institute of Planning and Evaluation for Technology in Food, Agriculture and Forestry (IPET), through the Animal Disease Management Technology Advancement Support Program, funded by the Ministry of Agriculture, Food and Rural Affairs (MAFRA) (Project No. 122013-2).

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