TY - JOUR
T1 - Australian perspectives on artificial intelligence in veterinary practice
AU - Currie, Geoff
AU - Hespel, Adrien-Maxence
AU - Carstens, Ann
N1 - Publisher Copyright:
© 2023 American College of Veterinary Radiology.
PY - 2023/5
Y1 - 2023/5
N2 - 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.
AB - 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.
KW - artificial intelligence
KW - convolutional neural network
KW - deep learning
KW - machine learning
KW - radiography
KW - veterinary
KW - Algorithms
KW - Animals
KW - Veterinary Medicine/organization & administration
KW - Artificial Intelligence
KW - Australia
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U2 - 10.1111/vru.13234
DO - 10.1111/vru.13234
M3 - Article
C2 - 37022301
SN - 1058-8183
VL - 64
SP - 473
EP - 483
JO - Veterinary Radiology and Ultrasound
JF - Veterinary Radiology and Ultrasound
IS - 3
ER -