The MaML Podcast - Medicine & Machine Learning

Spezi (Stanford CardinalKit) - An Open Source Framework for Digital Health


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CardinalKit (now Spezi) is an open-source framework for Digital Health Applications and Research. They were recently featured in the news for releasing HealthGPT, an experimental iOS app that lets you query your health data. Spezi is housed in the Stanford Byers Center for Biodesign and directed by Oliver Aalami, MD with Vishnu Ravi, MD as lead architect. Also joining us on this interview is postdoc Paul Schmiedmayer, PhD.


Spezi provides a suite of tools to build modern, interoperable digital health tools from the ground up, from the app itself to storing and analyzing collected data in the cloud. It is designed to accelerate rapid prototyping of digital health applications by reducing costs by as much as 75% (~$150,000) and timelines by 12 months.


Host: David Wu

Twitter: @davidjhwu 

Audio Producer + Video Editor + Art: Saurin Kantesaria

Instagram: saorange314

Social Media: Nikhil Kapur


Time Stamps:

00:58 - The expertise behind Spezi (CardinalKit)

08:03 - Healthcare has a lack of data standardization + Why you should know about HL7 FHIR

14:13 - How did Spezi (CardinalKit) become what it is today?

18:26 - Drink Spezi!

19:53 - Making code/healthcare data more modular and user-friendly

26:40 - Translating a med student's sensor research to a useable device for kids with cerebral palsy

31:20 - From a $40,000 eczema patch test in clinic to a completely at-home test

35:45 - Using healthGPT to make health data easy to understand for patients (LLM on FHIR)

42:35 - How do you deal with privacy issues?

49:33 - What do you think the future of AI in medicine will look like in 10-20 years?

52:00 - Applications where using only an LLM doesn't always work (a case for hybrid systems)

55:30 - What brings you joy?

58:43 - What makes a successful digital health team?




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The MaML Podcast - Medicine & Machine LearningBy Twitter - @themamlpodcast | TikTok - @maml_podcast

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