Artificial intelligence (AI) is quite a buzzword these days, with AI technology increasingly being applied to all aspects of information technology, affecting every corner of our day-to-day lives, including veterinary diagnostic imaging and radiation oncology.
Veterinary medicine, including veterinary diagnostic imaging and radiation oncology, is no exception. Advances in data processing now mean that enormous amounts of visual data can be processed and analyzed as never before. Artificial intelligence techniques are being actively developed and implemented in veterinary radiology, namely for improving the quality of our diagnostic images, the efficiency of our workflow and the way the images of our patients are interpreted. Specific applications are also on the horizon in veterinary radiation oncology for treating our cancer patients.
ACVR and ECVDI Position Statement on Artificial Intelligence
The ACVR and ECVDI support the development and use of ethical and transparent AI in veterinary diagnostic imaging and radiation oncology applications. The colleges acknowledge the potential positive transformational power of AI.
To best support veterinary teams and ensure patient safety, AI should be developed in accordance with the guiding principles of good machine learning practice.1 In doing so, AI systems should adhere to the guiding principles of transparency for machine learning–enabled medical devices.
The ACVR and ECVDI believe that AI systems should always be used with a qualified veterinary professional in the loop. In veterinary diagnostic imaging, board-certified radiologists are best suited to evaluate the output of computer-aided diagnostic tools. The same is true of board-certified radiation oncologists for evaluation of computer-assisted strategies in the planning, delivery, and quality assurance of radiation treatments for animals.
Artificial intelligence systems that do not ensure safe and secure handling of patient data; do not provide transparency of their underlying methodology, training, and testing sets; do not allow postimplementation monitoring as defined by good machine learning practices; and do not allow transparency for machine learning–enabled medical devices1,2 should not be used in veterinary practice. There is currently no commercially available product for diagnostic imaging that meets these standards.
The ACVR and ECVDI support ongoing research and encourage the publication of both internal documentation and external validation of AI tools in high-quality veterinary journals, including that of our colleges, Veterinary Radiology and Ultrasound.
The ACVR and ECVDI urge the need for unbiased, third-party evaluations of AI tools to establish trust and ensure that these technologies meet the highest standards of clinical effectiveness.
Veterinarians should exercise caution when using AI in diagnostic imaging and must understand the limitations of the systems they are using. The legal responsibility of decisions made from any AI system has yet to be determined but is likely to have some degree of responsibility for veterinarians themselves rather than developers of the AI alone.
Click here to access our open access publication in JAVMA.
Special Issue – Artificial Intelligence
In December 2022, Veterinary Radiology & Ultrasound, the official journal of the American College of Veterinary Radiology (ACVR) and European College of Veterinary Diagnostic Imaging (ECVDI), published an open access special issue focusing on artificial intelligence. The journal articles are free to the public for reading and download.
Publicly available presentations from the AI Forum at the 2021 ACVR Conference