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Deep learning-based imaging diagnostics with Lily Peng (Google Health)

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Manage episode 268873327 series 2769784
Content provided by Anika Gupta. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Anika Gupta or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.

In 2016, a team at Google Health led by Product Manager Lily Peng accurately predicted diabetic retinopathy in patients solely from images of their eyes. Today I chat with Lily about this work in diagnosing diabetic retinopathy by tapping into advances in deep learning, what factors determine whether a medical problem is well-suited to machine learning tasks, and the iterative process to achieve model performance in the context of a clinical environment. We also discuss tactics to effectively deploy such technologies in resource-poor regions in a sustainable way.

Check out the glossary of terms, definitions, and resources (and get a sneak peak of the future conversations lined up!) here: bit.ly/datapulse-glossary

--- Support this podcast: https://podcasters.spotify.com/pod/show/the-data-pulse/support
  continue reading

25 episodes

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Manage episode 268873327 series 2769784
Content provided by Anika Gupta. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Anika Gupta or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.

In 2016, a team at Google Health led by Product Manager Lily Peng accurately predicted diabetic retinopathy in patients solely from images of their eyes. Today I chat with Lily about this work in diagnosing diabetic retinopathy by tapping into advances in deep learning, what factors determine whether a medical problem is well-suited to machine learning tasks, and the iterative process to achieve model performance in the context of a clinical environment. We also discuss tactics to effectively deploy such technologies in resource-poor regions in a sustainable way.

Check out the glossary of terms, definitions, and resources (and get a sneak peak of the future conversations lined up!) here: bit.ly/datapulse-glossary

--- Support this podcast: https://podcasters.spotify.com/pod/show/the-data-pulse/support
  continue reading

25 episodes

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