Australian perspectives on artificial intelligence in veterinary practice

Show simple item record

dc.contributor.author Currie, Geoff
dc.contributor.author Hespell, Adrien-Maxence
dc.contributor.author Carstens, Ann
dc.date.accessioned 2023-10-17T16:27:58Z
dc.date.issued 2023-05
dc.description DATA AVAILABILITY: Data are available upon reasonable request. en_US
dc.description.abstract While artificial intelligence (AI) and recent developments in deep learning (DL) have sparked interest in medical imaging, there has been little commentary on the impact of AI on the veterinarian and veterinary imaging technologists. This survey study aimed to understand the attitudes, applications, and concerns among veterinarians and radiography professionals in Australia regarding the rapidly emerging applications of AI. An anonymous online survey was circulated to the members of three Australian veterinary professional organizations. The survey invitations were shared via email and social media with the survey open for 5 months. Among the 84 respondents, there was a high level of acceptance of lower order tasks (e.g., patient registration, triage, and dispensing) and less acceptance of high order task automation (e.g., surgery and interpretation). There was a low priority perception for the role of AI in higher order tasks (e.g., diagnosis, interpretation, and decision making) and high priority for those applications that automate complex tasks (e.g., quantitation, segmentation, reconstruction) or improve image quality (e.g., dose/noise reduction and pseudo CT for attenuation correction). Medico-legal, ethical, diversity, and privacy issues posed moderate or high concern while there appeared to be no concern regarding AI being clinically useful and improving efficiency. Mild concerns included redundancy, training bias, transparency, and validity. Australian veterinarians and veterinary professionals recognize important applications of AI for assisting with repetitive tasks, performing less complex tasks, and enhancing the quality of outputs in medical imaging. There are concerns relating to ethical aspects of algorithm development and implementation. en_US
dc.description.department Companion Animal Clinical Studies en_US
dc.description.embargo 2024-04-06
dc.description.uri https://wileyonlinelibrary.com/journal/vru en_US
dc.identifier.citation Currie, G., Hespel, A.-M. & Carstens, A. Australian perspectives on artificial intelligence in veterinary practice. Veterinary Radiology & Ultrasound 2023; 64: 473–483. https://doi.org/10.1111/vru.13234. en_US
dc.identifier.issn 1058-8183 (print)
dc.identifier.issn 1740-8261 (online)
dc.identifier.other 10.1111/vru.13234
dc.identifier.uri http://hdl.handle.net/2263/92953
dc.language.iso en en_US
dc.publisher Wiley en_US
dc.rights © 2023 American College of Veterinary Radiology. This is the pre-peer reviewed version of the following article : Australian perspectives on artificial intelligence in veterinary practice. Veterinary Radiology & Ultrasound 2023; 64: 473–483. https://doi.org/10.1111/vru.13234. The definite version is available at : http://wileyonlinelibrary.com/journal/vru. en_US
dc.subject Artificial intelligence en_US
dc.subject Convolutional neural network en_US
dc.subject Deep learning en_US
dc.subject Machine learning en_US
dc.subject Radiography en_US
dc.subject Veterinary en_US
dc.subject Artificial intelligence (AI) en_US
dc.title Australian perspectives on artificial intelligence in veterinary practice en_US
dc.type Postprint Article en_US


Files in this item

This item appears in the following Collection(s)

Show simple item record