So I think that there’s a lot of transformation in the next decade in two domains. One is research and two is operations. And it might make sense to talk about the latter one first, in that I do think that AI developments will be financially motivated and how to decrease inefficiencies. So first, I think we’re going to be seeing a lot of documentation – increasing the speed of writing my notes, for example, and that’s going to increase the volume of MPN patients that we can see...
So I think that there’s a lot of transformation in the next decade in two domains. One is research and two is operations. And it might make sense to talk about the latter one first, in that I do think that AI developments will be financially motivated and how to decrease inefficiencies. So first, I think we’re going to be seeing a lot of documentation – increasing the speed of writing my notes, for example, and that’s going to increase the volume of MPN patients that we can see. That’s the first and foremost.
But outside of that, in the research domain, I think us as clinical investigators, especially here at the Workshop of the Carolinas, are really interested in developing AI tools for clinically relevant outcomes. I think we’ll be seeing more AI tools looking at digital pathology for making a diagnosis and even doing more such as predicting genetic state from the digital pathology and potentially even predicting therapy response. My gold standard, my hope in the future is that we will have some tool to say who’s going to respond to upfront cytoreduction therapy across all the disease states polycythemia vera, essential thrombocythemia, and primary myelofibrosis. I think we can do it, but I do think it’s going to take that 10 years that you’re asking for, not in the next two, three, five years.
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