Franziska Michor

"I think we’re just at the beginning of the revolution that machine learning is going to bring about in cancer biology and in medicine. 

"And there are extremely powerful tools that we can use. And the applicability of those tools, of course, depends on the question that you want to ask. There’s lots of prediction tasks that are quite amenable to machine learning approaches. 

"For instance, in radiology, right? If you are trying to identify which speckle on a CT scan or an MRI actually are tumor versus maybe something else, maybe a bile duct, maybe some other structure. There’s extreme talent that radiologists have, and experience, that they have to deploy in order to accurately disentangle all of these different structures. But maybe that can be aided by machine learning approaches that are trained on large enough, gold-standard labeled data sets, such that maybe later on we can do this automatically. 

"We’re not quite there yet, but I think a lot of progress has been made lately in order to answer questions like that. 

"And so I’m super excited about the future and what these really powerful technologies will be able to bring to the table." 


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