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Artificial intelligence feasibility in veterinary medicine: A systematic review
Fayssal Bouchemla1, Sergey Vladimirovich Akchurin2, Irina Vladimirovna Akchurina2
1Department of Animal Disease, Veterinarian and Sanitarian Expertise, Faculty of Veterinary Medicine, Vavilov Saratov State University of Genetic, Biotechnology and Engineering Saratov, Russia.
Veterinary World
|November 29, 2023
Summary
Artificial intelligence (AI) in veterinary medicine shows promise across diagnostics, education, and animal health, but faces challenges. Increased AI integration is recommended, focusing on user-friendly models to enhance veterinary practice.
Area of Science:
- Veterinary Medicine
- Artificial Intelligence
- Life Sciences
Background:
- Artificial intelligence (AI) is increasingly vital in life sciences, especially medicine and healthcare.
- This study systematically reviews AI applications in veterinary medicine to identify challenges and promote professional awareness.
Purpose of the Study:
- To systematically review and critically analyze the literature on AI in veterinary medicine.
- To assess the challenges and effects of AI implementation in veterinary practice.
- To foster professional awareness regarding AI's role in veterinary medicine.
Main Methods:
- Systematic review of multiple electronic databases (PubMed, Embase, Google Scholar, Cochrane Library, Elsevier) up to March 22, 2023.
- Adherence to PRISMA and Cochrane guidelines for systematic reviews.
- Careful study design emphasizing evidence quality and population heterogeneity.
Main Results:
- 385 of 883 citations were reviewed, covering diagnostics, education, animal production, epidemiology, animal health, welfare, pathology, and microbiology.
- Included studies showed variable quality and risk of bias.
- AI algorithms faced criticism regarding their generated conclusions despite noted performance strengths.
Conclusions:
- AI shows performance strengths but also areas for criticism in veterinary medicine.
- Increased AI integration is recommended, but it should augment, not replace, veterinary professionals.
- Future AI models should feature flexible data input for enhanced user interaction and error reduction.
