Before anything can be discussed about why the time for AI in healthcare has arrived, we need to say that if we did not have an increasing amount of digitized data, none of the other factors would matter. AI needs large amounts of data and for the first time in human history, healthcare is producing large amounts of digital data (Figure 1.) Now, a lot of this data is unstructured and fragmented. Those are big issues to be sure, but we are headed in the right direction. And, there is enough structured data in radiology, pathology, ophthalmology, etc for us to start developing and deploying the initial set of AI applications. Also, emergence of AI solutions is highlighting how data should be captured and organized to facilitate the use of AI. As more and more providers see the benefits of AI, the value of the extra effort to capture and organize data for the use of AI will become more obvious. It is estimated that only 5% of this data has been analyzed so far. Lots to look forward to!
Figure 1
Figure 2
Figure 2 shows the rapid rise in investments in AI in healthcare over the last decade. This only represents private investments but public investments in AI in general and AI in healthcare has increased dramatically. It is important that we see commercially successful applications of AI in Healthcare in the near future as there is always concern that large amounts of investments without commensurate return on that investment could mean that investors will stop pouring money into this sector.
