In the 1970s patients were relatively healthy with most having only one disease with one or two treatments available. In the 2020s we have transitioned to a time where people are living longer with multiple comorbidities and there are tons of treatments available. The question is how are doctors choosing? What happens if they don't have good information? We have challenges of sharing data, challenges of interoperability, challenges of accuracy. We can see where the industry needs to improve but this is a long-term commitment that will take decades.

Dr. Dan Riskin, Verantos

AI is somewhat analogous to driving. You can easily drive without a GPS, especially if it's somewhere close and familiar. But most patients are complicated and it helps a great deal to have the support of data science. It's like driving with a GPS to a place that's far, that you don't know and you're not familiar with.

Dr. Anthony Chang, AIMed

Today what you have is electronic health records that are fundamentally big, dumb data repositories that aren't easy to use. Think about Silicon Valley. If you said to anybody, your system is so complex you need a scribe to help you enter the data. They would look at you and say, thats the picture child for bad software.

Glen Tullman, Transcarent