Artificial intelligence in veterinary medicine is an emerging field. Machine learning, a subfield of artificial intelligence, allows computer programs to analyze large imaging datasets and learn to perform tasks relevant to veterinary diagnostic imaging. This review summarizes the small, yet...
Author(s)
Hennessey, E.; Difazio, M.; Hennessey, R.; Cassel, N.
Publisher
Wiley, Boston, USA
Citation
Veterinary Radiology & Ultrasound, 2022, 63, s1, pp 851-870
Food security is one of the priorities of every country in the World. However, different factors are making it difficult to meet global targets on food security. Some unprecedented shocks are encumbering food security at the global level. Various interventions have been applied toward food security ...
Author(s)
Kutyauripo, I.; Rushambwa, M.; Chiwazi, L.
Publisher
Elsevier B.V., Amsterdam, Netherlands
Citation
Journal of Agriculture and Food Research, 2023, 11,
Evidence-based medicine, outcomes management, and multidisciplinary systems are laying the foundation for radiology on the cusp of a new day. Environmental and operational forces coupled with technological advancements are redefining the veterinary radiologist of tomorrow. In the past several...
Author(s)
Wilson, D. U.; Bailey, M. Q.; Craig, J.
Publisher
Wiley, Boston, USA
Citation
Veterinary Radiology & Ultrasound, 2022, 63, s1, pp 897-902
ChatGPT adds to the list of artificial intelligence-based systems designed to perform specific tasks and answer questions by interacting with users (Apple's Siri, Amazon's Alexa, Google's Assistant and Bard, Microsoft's Cortana, IBM's Watson, Bixby from Samsung, among others). ChatGPT works using...
Author(s)
Siche, R.; Siche, N.
Publisher
Universidad Nacional de Trujillo, Trujillo, Peru
Citation
Scientia Agropecuaria, 2023, 14, 1, pp 111-116
Artificial Intelligence (AI) has become an important tool for optimising breeding processes in several areas of animal production. In this thesis, we have presented examples from the literature, mainly for the identification and counting of cattle. The individual identification of animals, the...
Author(s)
Bence, T.; Balázs, K.; István, S.; János, T.
Publisher
Szent István University, Gödöllo, Hungary
Citation
Animal Welfare, Ethology and Housing Systems, 2022, 18, 1, pp 51-63
Farm animals, numbering over 70 billion worldwide, are increasingly managed in large-scale, intensive farms. With both public awareness and scientific evidence growing that farm animals experience suffering, as well as affective states such as fear, frustration and distress, there is an urgent need ...
Author(s)
Neethirajan, S.
Publisher
MDPI AG, Basel, Switzerland
Citation
Animals, 2022, 12, 6,
Veterinary medicine is a broad and growing discipline that includes topics such as companion animal health, population medicine and zoonotic diseases, and agriculture. In this article, we provide insight on how artificial intelligence works and how it is currently applied in veterinary medicine. We ...
Author(s)
Basran, P. S.; Appleby, R. B.
Publisher
American Veterinary Medical Association, Schaumburg, USA
Citation
American Journal of Veterinary Research, 2022, 83, 5, pp 385-392
This special issue contains 17 articles discussing the use of precision agriculture methods with topics such as: artificial intelligence; machine learning for crop classification; use of digital image for leaf phosphorus content classification; VIS-NIR spectroscopy and machine learning for fruit...
Publisher
Sociedade Brasileira de Engenharia Agrícola (SBEA), Jaboticabal, Brazil
Citation
Engenharia Agrícola, 2022, 42, Numero Especial, pp unpaginated
The prevalence and pervasiveness of artificial intelligence (AI) with medical images in veterinary and human medicine is rapidly increasing. This article provides essential definitions of AI with medical images with a focus on veterinary radiology. Machine learning methods common in medical image...
Author(s)
Hespel, A. M.; Zhang YouShan; Basran, P. S.
Publisher
Wiley, Boston, USA
Citation
Veterinary Radiology & Ultrasound, 2022, 63, s1, pp 817-827
Artificial Intelligence and machine learning are novel technologies that will change the way veterinary medicine is practiced. Exactly how this change will occur is yet to be determined, and, as is the nature with disruptive technologies, will be difficult to predict. Ushering in this new tool in a ...
Author(s)
Cohen, E. B.; Gordon, I. K.
Publisher
Wiley, Boston, USA
Citation
Veterinary Radiology & Ultrasound, 2022, 63, s1, pp 840-850