Keynote Lecture - Parminder S. Basran

KEYNOTE LECTURE

Parminder S. Basran

Cornell University College of Veterinary Medicine, US

Artificial intelligence holds transformative potential for veterinary medicine, yet significant barriers prevent its widespread adoption. We examine why AI tools remain underutilized in veterinary settings despite demonstrated benefits in diagnostic accuracy, workflow efficiency, and patient care in human medicine. By exploring the technical, practical, and educational challenges that impede the integration of AI into routine clinical workflows, we identify pathways toward integrating AI technologies in veterinary medicine while avoiding pitfalls observed in human medicine.

A central challenge lies in data interoperability across veterinary medicine. Unlike standardized formats such as DICOM used in medical imaging, veterinary data types are less structured and often lack standards, which hinders the development of computer vision and machine learning models. The absence of common data frameworks complicates efforts to integrate AI tools with electronic health records and existing clinical workflows. The integration of multimodal data, which combines medical imaging, laboratory results, clinical notes, and sensor-derived information, has the potential to improve diagnostics; however, simply merging these data types does not guarantee improved performance in multimodal machine learning. We illustrate the effects of disparate multimodal data types and the challenges of multi-institutional data in studies of feline gastrointestinal diseases using ultrasound, biomarker, and biopsy data. Bridging the gap between AI potential and practical implementation requires coordinated efforts across technology development, policy formation, education reform, and interdisciplinary collaboration.

Dr. Parminder S. Basran is an Associate Research Professor at Cornell University's College of Veterinary Medicine, a Fellow of the Canadian College of Physicists in Medicine, and a Fellow of the American Association of Physicists in Medicine. He obtained his Ph.D. from the University of Calgary (2002), and his expertise spans radiation dosimetry, medical image processing, AI, and education. Dr. Basran is intensely focused on translating medical physics knowledge and practice well beyond human medicine to other disciplines, such as livestock and veterinary medicine, and other dimensions under a "One Health" paradigm. His lab, Veterinary AI in Diagnostic Imaging and Radiotherapy (VAIDER Lab), collaborates with radiologists, pathologists, computing scientists, oncologists, and other healthcare disciplines in both human and veterinary medicine. He is an ardent advocate for the global dissemination of medical physics knowledge, with projects focused on democratizing access to education and data.