---
title: "Webinar: Explainable AI for Disease Prediction in Pets"
description: "Webinar: Explainable AI for Disease Prediction in Pets"
image: https://spryfox.ai/hubfs/Blog%20header%20%26%20feature%201200x627.png
---

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# Webinar: Explainable AI for Disease Prediction in Pets

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 by [Spryfox](https://spryfox.ai/en/blog/author/spryfox)

6/11/26, 10:52 AM

#### If you work in a regulated industry and you're trying to figure out where AI actually fits, this webinar is for you.

We hosted a live session with the team behind [Fetch Health Forecast](https://www.fetchpet.com/health), an AI product for [Fetch Pet Insurance](https://www.fetchpet.com/) that predicts disease risk in dogs, built on 17 years of insurance claims data.

It's a real case study in how you build predictive AI that domain experts, compliance teams, and regulators can actually trust, because explainability was engineered in from the start.

Joining Dr. Christian Debes are two of the veterinary specialists who shaped the model from the inside: [Dr. Audrey Ruple](https://spryfox.ai/hs-fs/hubfs/Dr.%20Audrey%20Ruple.png?width=400&height=400&name=Dr.%20Audrey%20Ruple.png), Metcalf Professor of Veterinary Medical Informatics, Virginia Tech & Fetch Pet Insurance Vet Board Advisor, and [Dr. Aliya McCullough](https://www.linkedin.com/in/aliya-mccullough-dvm-ms-4b2b45152/), Chief Veterinary Officer & Director of Veterinary Affairs, Fetch Pet Insurance.

We covered:

- Why explainability starts with the domain expert, not the deployment checklist
- The case for building simple models deliberately, and what they reveal
- How to translate model outputs into decisions stakeholders can actually act on

If your AI models need to be defensible, this is the session to attend.

Watch the full webinar on-demand below.<https://spryfox.ai/en/webinar-explainable-ai-for-disease-prediction-in-pets?hsLang=en>

 

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[Insurance,](https://spryfox.ai/en/blog/tag/insurance) [Case Study,](https://spryfox.ai/en/blog/tag/case-study) [Webinar](https://spryfox.ai/en/blog/tag/webinar)

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**[Spryfox](https://spryfox.ai/en/blog/author/spryfox)**  
 6/11/26, 10:52 AM

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