Gut Meets Gigabyte: Enhancing Clinical Decisions with AI
0.5 CE Credit Hour / Kathleen Allison-Black, DVM
Kathleen Allison-Black, DVM
Dr. Kate Allison is a veterinarian, writer, and unapologetic data nerd with more than two decades of experience across emergency and critical care, shelter medicine, and general practice. Her work sits at the intersection of medicine, tech, and public health—where the algorithms meet the animals.
Known internationally for her leadership in zoonotic disease and outbreak response, Dr. Allison has become a leading voice in the veterinary conversation around emerging threats—most recently, the evolving risk of Highly Pathogenic Avian Influenza (HPAI H5N1) in companion animals, particularly cats. She lectures nationally on infectious disease preparedness, the use of AI in veterinary medicine, and building smarter communication and workflow systems for clinics and shelters.
Whether she’s helping a shelter build an outbreak protocol or teaching practitioners how to make peace with their PIMS data, her through-line is always the same: clarity, compassion, and evidence-based action. She’s also the creator of Pawgorithms, a Substack dedicated to practical, algorithm-driven approaches to modern veterinary medicine, and is currently developing AIpowered tools for disease surveillance and clinical decision support
Overview:
Good medicine lives at the intersection of instinct and information. In this session, we’ll explore how AI tools can help you harness data—patient histories, lab results, imaging trends—to support sound, evidence-based decisions. Learn four strategies for integrating AI insights into your everyday case management, balancing innovation with clinical judgment and ethics. Because the best care doesn’t replace your brain—it just gives it better data to think with.
Learning Objectives:
At the conclusion of this session, participants will be able to:
- Describe the role of AI in supporting clinical decision-making in veterinary medicine.
- Identify opportunities where AI tools can enhance diagnostic and treatment planning.
- Analyze patient data using AI-supported insights to inform clinical decisions
- Apply AI tools safely and ethically to guide case management and optimize outcomes
- Evaluate the effectiveness of AI-assisted decision-making and adjust workflows for improved patient care
This course is RACE-approved for 0.5 continuing education credits hours in jurisdictions that accept RACE-approval.
