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2000
Volume 21, Issue 1
  • ISSN: 1574-3624
  • E-ISSN: 2212-389X

Abstract

Artificial intelligence (AI) is a rapidly expanding field of innovative technology that has great potential to transform many different scientific and technological fields. AI can be used in veterinary treatment and animal disease management to produce better outcomes for people and animals. AI can help in many disciplines, including genetics, cancer research, epidemiology, disease surveillance, therapy and vaccine development, studies on antimicrobial resistance (AMR), and is presented as an essential tool to address worldwide health issues in many fields. Most investigational AI-driven animal care research focuses on data collection, processing, evaluation, and analysis for animal behaviour detection, disease surveillance, growth estimation, and environmental monitoring. This paper describes and investigates the potential consequences of different elements of AI on animal disease and how AI is developing across many disciplines; the most prominent are deep learning and machine learning. Machine learning (ML) can be used to create models capable of predicting the future through algorithms that discover patterns in data. The development of AI technologies has sped up the process of drug discovery by locating possible therapeutic targets and improving candidate medications. This paper discusses these advancements while also analyzing the opportunities that lie ahead for artificial intelligence in the field of animal disease control. We also highlight the potential of AI to preserve the wellness of humans and animals across nations, highlighting the role AI plays in advancing the management of animal illnesses.

© 2026 Bentham Science Publishers
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2025-07-11
2026-02-20

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Significance of Artificial Intelligence in Animal Disease Recognition
Current Signal Transduction Therapy 21, E15743624362164 (2026); https://doi.org/10.2174/0115743624362164250630194443
/content/journals/cst/10.2174/0115743624362164250630194443
/content/journals/cst/10.2174/0115743624362164250630194443
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  • Article Type:     Review Article
Keyword(s): animal disease; antimicrobial resistance (AMR); Artificial intelligence (AI); deep learning; epidemiological; machine learning

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