The second offering we’re showing is called IBM Watson Imaging Synopsis. That is a radiology built artificial intelligence platform for providing relevant EMR summarization. The problem that we’re solving is like any other professional, radiologists have way too much information to deal with. They don’t have the time to read the EMR, and peer-review literature shows that if they do take the time to read the full EMR and read every progress note, an alarmingly high precision of time, 20-25 percent, shows they actually may change their opinion which is scary. So, we’ve built a product concept to show what Watson can do to summarize the EMR and it’s clinically relevant which is key. We’re getting very good feedback. That product’s coming out in the second quarter of 2018. You can see that in the booth. We will introduce it for general radiology first, and then we’ll do specialty radiology and cardiology after that. I like to say version one is going to be great and version five is going to be amazing. There’s this iterative process. And then we’ll do chest radiology, mammograms, the different specialties.

The third option we’re showing is the first offering of our breast adviser. In our business, we are focusing on diseases where imaging is a primary diagnostic tool, where a lot of people are getting scanned and where there’s a problem to solve that AI can help. We’re looking at breast, lung, brain, eyes. Our first breast adviser product will be coming off the truck later this year. And we’re starting by using our algorithms to look at the current image, the prior image, calculate breast density, and we are showing the ability to prioritize a worklist based on potential pathology. The reason that’s important is because when a woman comes in for a mammogram, if she has dense breast tissue or if she has something there, she often needs to go for another test like an ultrasound. You want to do that when she’s there. It’s not a great experience to drive all the way in, get scanned and get a call later saying you need to come back in. It’s also pretty anxiety provoking. We’re trying to reduce the number of callbacks happening and improve the overall experience for the patient and for the imaging practice. You can see that in the booth as well.

HCB News: Since IBM's acquisition of Merge it has been at the forefront of medical imaging machine learning. What does it feel like to look around and see an entire industry is now following that path?

ST: We’ve seen a ton of announcements coming up to this show and during this show about the use of AI and imaging. It makes a lot of sense, obviously. We’re big believers in it. But given the amount of time we’ve been working on it, we have some concerns about the claims people have been making. We have some concerns about where is the value proposition. You can do a lot with AI and deep learners but you've got to make sure that you’re solving the right problem. You’ve got to be thoughtful around the question, ‘Is this something that needs to be solved?’

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