Episode: Building AI-Driven Health Products That Clinicians and Consumers Can Trust
Guest: Cazandra Aporbo, MS – Head of Data, FoXX Health

Summary
In this episode, Kelly, Kristi, and Alex sit down with Cazandra Aporbo, Head of Data from FoXX Health to talk about what it actually takes to build AI for healthcare that people trust. They dig into the “diagnostic odyssey” for women (why it can take 7–10 years to get a diagnosis), how fragmented and biased health data really is, and why the answer isn’t to pretend bias doesn’t exist—but to make it visible and explainable. Cazandra walks through how FoXX is co-building an AI-powered women’s health companion app that supports clearer health insights for women.

What you’ll hear about

• Why AI in health has higher stakes than other industries
• The gap FoXX is trying to close: consumer data ➜ clinical decision support
• Making biased, fragmented data transparent instead of hiding it
• Validating AI models for different use cases (clinical vs consumer)
• Designing AI outputs people can actually understand and act on
• Why “your normal” matters more than population averages

Key quotes

• “We can’t collect data that doesn’t exist—so we make the bias visible.”
• “Validation isn’t a checkbox, it’s a continuous relationship with the data.”
• “The goal is for women to understand their normal, not the average woman.”
  

Who it’s for
Product leaders in digital health, AI/ML folks working with clinical or patient-generated data, founders building women’s health apps, and clinicians trying to make sense of all the ‘AI in healthcare’ noise.

Links/mentions

• FoXX Health (women’s health companion app + community “The Den”)
• Concepts: diagnostic odyssey, ethical AI, model monitoring, consumer-to-clinical data bridge
  

Length: ~40 minutes