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AI in Vet Med: From Bark to Bytes
Manage episode 473174598 series 3395438
Artificial intelligence is no longer the future of veterinary medicine—it's very much the present. In this captivating discussion with guest editors Casey Cazer, Parminder Basran, and Renata Ivanek, we explore the groundbreaking AJVR supplemental issue "From Bark to Bytes: Artificial Intelligence Transforming Veterinary Medicine."
The conversation reveals how AI applications already extend far beyond the clinical notes scribes that many practitioners might be familiar with. Veterinarians are now using AI-assisted stethoscopes to detect bovine respiratory disease, employing machine learning algorithms to predict Lyme disease risk patterns, and leveraging artificial intelligence to fill gaps in antimicrobial resistance surveillance data. Each application demonstrates how this technology can enhance clinical decision-making while accelerating vital research.
Our guests emphasize that successful AI implementation requires multidisciplinary collaboration, quality data, and thoughtful integration. "Garbage in, garbage out" remains a fundamental principle—without standardized, high-quality data, even the most sophisticated AI tools will produce unreliable results. The ethical dimensions of AI in veterinary medicine also take center stage in our discussion, from ensuring data privacy and informed consent to recognizing inherent biases and maintaining the veterinarian's ultimate responsibility for patient care.
For practitioners curious about incorporating AI tools into their workflow, our experts recommend starting with well-researched technologies, implementing them gradually, and evaluating how they affect the veterinarian-client relationship. As this field continues its rapid evolution, staying informed through resources like this supplemental issue becomes increasingly crucial for veterinarians who want to harness AI's potential while navigating its challenges. Join the conversation at the second Symposium for Artificial Intelligence in Veterinary Medicine at Cornell University (May 16-18, 2025) to explore how these technologies can help shape the future of animal healthcare.
INTERESTED IN SUBMITTING YOUR MANUSCRIPT TO JAVMA ® OR AJVR ® ?
JAVMA ® : https://avma.org/JAVMAAuthors
AJVR ® : https://avma.org/AJVRAuthors
FOLLOW US:
JAVMA ® :
Facebook: Journal of the American Veterinary Medical Association - JAVMA | Facebook
Instagram: JAVMA (@avma_javma) • Instagram photos and videos
Twitter: JAVMA (@AVMAJAVMA) / Twitter
AJVR ® :
Facebook: American Journal of Veterinary Research - AJVR | Facebook
Instagram: AJVR (@ajvroa) • Instagram photos and videos
Twitter: AJVR (@AJVROA) / Twitter
JAVMA ® and AJVR ® LinkedIn: https://linkedin.com/company/avma-journals
Chapters
1. Introduction to AI in Veterinary Medicine (00:00:00)
2. Overview of the AJVR AI Supplemental Issue (00:03:26)
3. Origins of the AI Veterinary Symposium (00:08:15)
4. Diverse Applications of AI in Vet Med (00:15:05)
5. Future Research Directions in AI (00:20:37)
6. Data Quality and Ethics in AI (00:28:42)
7. Closing Thoughts and Future Symposium (00:35:13)
149 episodes
Manage episode 473174598 series 3395438
Artificial intelligence is no longer the future of veterinary medicine—it's very much the present. In this captivating discussion with guest editors Casey Cazer, Parminder Basran, and Renata Ivanek, we explore the groundbreaking AJVR supplemental issue "From Bark to Bytes: Artificial Intelligence Transforming Veterinary Medicine."
The conversation reveals how AI applications already extend far beyond the clinical notes scribes that many practitioners might be familiar with. Veterinarians are now using AI-assisted stethoscopes to detect bovine respiratory disease, employing machine learning algorithms to predict Lyme disease risk patterns, and leveraging artificial intelligence to fill gaps in antimicrobial resistance surveillance data. Each application demonstrates how this technology can enhance clinical decision-making while accelerating vital research.
Our guests emphasize that successful AI implementation requires multidisciplinary collaboration, quality data, and thoughtful integration. "Garbage in, garbage out" remains a fundamental principle—without standardized, high-quality data, even the most sophisticated AI tools will produce unreliable results. The ethical dimensions of AI in veterinary medicine also take center stage in our discussion, from ensuring data privacy and informed consent to recognizing inherent biases and maintaining the veterinarian's ultimate responsibility for patient care.
For practitioners curious about incorporating AI tools into their workflow, our experts recommend starting with well-researched technologies, implementing them gradually, and evaluating how they affect the veterinarian-client relationship. As this field continues its rapid evolution, staying informed through resources like this supplemental issue becomes increasingly crucial for veterinarians who want to harness AI's potential while navigating its challenges. Join the conversation at the second Symposium for Artificial Intelligence in Veterinary Medicine at Cornell University (May 16-18, 2025) to explore how these technologies can help shape the future of animal healthcare.
INTERESTED IN SUBMITTING YOUR MANUSCRIPT TO JAVMA ® OR AJVR ® ?
JAVMA ® : https://avma.org/JAVMAAuthors
AJVR ® : https://avma.org/AJVRAuthors
FOLLOW US:
JAVMA ® :
Facebook: Journal of the American Veterinary Medical Association - JAVMA | Facebook
Instagram: JAVMA (@avma_javma) • Instagram photos and videos
Twitter: JAVMA (@AVMAJAVMA) / Twitter
AJVR ® :
Facebook: American Journal of Veterinary Research - AJVR | Facebook
Instagram: AJVR (@ajvroa) • Instagram photos and videos
Twitter: AJVR (@AJVROA) / Twitter
JAVMA ® and AJVR ® LinkedIn: https://linkedin.com/company/avma-journals
Chapters
1. Introduction to AI in Veterinary Medicine (00:00:00)
2. Overview of the AJVR AI Supplemental Issue (00:03:26)
3. Origins of the AI Veterinary Symposium (00:08:15)
4. Diverse Applications of AI in Vet Med (00:15:05)
5. Future Research Directions in AI (00:20:37)
6. Data Quality and Ethics in AI (00:28:42)
7. Closing Thoughts and Future Symposium (00:35:13)
149 episodes
All episodes
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