Welcome to the Episode 304, part of the continuing series called “Behind the Scenes of the NetApp Tech ONTAP Podcast.”
With breast cancer, early detection is critical in survival and remission rates. If you can reduce the amount of time it takes to find cancerous cells by using AI/ML workflows, you can literally save lives. Laurence Yudkovitch (Laurence Yudkovitch, LinkedIn, @laurencey) joins us to discuss just how iCad is cutting cancer detection times down, increasing accuracy and reducing the workload of radiologists. Esteban Rubens (@esteban_aihc) from NetApp also joins us.
If you want a searchable transcript of the episode, check it out here (just set expectations accordingly):
Episode 304: Machine Learning in Breast Cancer Screening using iCad – Transcript not available currently
Just use the search field to look for words you want to read more about. (For example, search for “storage”)
Be sure to give us feedback (or if you need a full text transcript – Gong does not support sharing those yet) on the transcription in the comments here or via firstname.lastname@example.org! If you have requests for other previous episode transcriptions, let me know!
Tech ONTAP Community
We also now have a presence on the NetApp Communities page. You can subscribe there to get emails when we have new episodes.
Finding the Podcast
You can find this week’s episode here:
You can also find the Tech ONTAP Podcast on:
I also recently got asked how to leverage RSS for the podcast. You can do that here: