31 January 2024 | Olalekan Chris Akinsulie, Ibrahim Idris, Victor Ayodele Aliyu, Sammuel Shahzad, Olamilekan Gabriel Banwo, Seto Charles Ogunleye, Mercy Olorunshola, Deborah O. Okedoyin, Charles Ugwu, Ifeoluwa Peace Oladapo, Joy Olaoluwa Gbadegoye, Qudus Afolabi Akande, Pius Babawale, Sahar Rostami and Kehinde Olugboyega Soetan
The article discusses the potential applications of artificial intelligence (AI) in veterinary clinical practice and biomedical research. AI is highlighted as a transformative technology that can enhance veterinary care, improve animal health outcomes, and address global health challenges. In veterinary clinical practice, AI can be used for radiomics, disease diagnosis, zoonotic disease monitoring, epidemiology, and surveillance, as well as in artificial insemination and patient assessment. In biomedical research, AI is crucial for antimicrobial resistance (AMR) research, cancer research, genomic and vaccine development, and phytomedicinal and ethnomedicinal research. The article also addresses the limitations and challenges of implementing AI in veterinary medicine, such as data availability, regulatory frameworks, and ethical considerations. Despite these challenges, the integration of AI in veterinary medicine is expected to revolutionize the field, leading to more precise, efficient, and individualized care for animals.The article discusses the potential applications of artificial intelligence (AI) in veterinary clinical practice and biomedical research. AI is highlighted as a transformative technology that can enhance veterinary care, improve animal health outcomes, and address global health challenges. In veterinary clinical practice, AI can be used for radiomics, disease diagnosis, zoonotic disease monitoring, epidemiology, and surveillance, as well as in artificial insemination and patient assessment. In biomedical research, AI is crucial for antimicrobial resistance (AMR) research, cancer research, genomic and vaccine development, and phytomedicinal and ethnomedicinal research. The article also addresses the limitations and challenges of implementing AI in veterinary medicine, such as data availability, regulatory frameworks, and ethical considerations. Despite these challenges, the integration of AI in veterinary medicine is expected to revolutionize the field, leading to more precise, efficient, and individualized care for animals.