Predicting Cardiovascular Risk Factors from Eye Images with Ryan Poplin

800 800 This Week in Machine Learning & AI

In this episode, I’m joined by Google Research Scientist Ryan Poplin, who recently co-authored the paper “Prediction of cardiovascular risk factors from retinal fundus photographs via deep learning.”

In our conversation, Ryan details his work training a deep learning model to predict various patient risk factors for heart disease, including some surprising ones like age and gender. We also dive into some interesting findings he discovered with regards to multi-task learning, as well as his use of an attention mechanisms to provide explainability. This was a really interesting discussion that I think you’ll really enjoy!

Conference Update

You all know I travel to a ton of events each year, and event season is just getting underway for me. One of the events I’m most excited about is my very own AI Summit, the successor to the awesome Future of Data Summit event I produced last year. This year’s event takes place April 30th and May 1st, and is once again being held in Las Vegas, in conjunction with the Interop ITX conference.

This year’s event is much more AI focused, and is targeting enterprise line-of-business and IT managers and leaders who want to get smart on AI very quickly. Think of it as a two-day, no-fluff, Technical MBA in machine learning & AI. I’ll be presenting an ML & AI bootcamp, and I’ll have experts coming in to present mini workshops on computer vision, natural language processing and conversational applications, ML and AI for IoT and industrial applications, data management for AI, building an AI-first culture in your organization, and operationalizing ML and AI. For more information on the program visit twimlai.com/aisummit-interop-2018/.

About Ryan

Mentioned in the Interview

“More On That Later” by Lee Rosevere licensed under CC By 4.0

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