On Machine Learning and AI in Healthcare

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By Vic Nagjee, posted in Healthcare blog

There’s a lot of buzz — rightfully so! — around the potential for Machine Learning (ML) and Artificial Intelligence (AI) in healthcare. I’ve been watching this space for some time now, and I continue to be bullish on the prospects of ML/AI in the healthcare industry. Here, I’m going to write about my views on The Why of ML/AI, some examples of The Who in this space, and, finally, some thoughts on The How these practices are going to disrupt processes in healthcare. Oh, and I’ll also provide some thoughts on the infrastructure that’s needed to make this all happen, because, those who know me will know my thoughts on infrastructure, viz. Infrastructure is Nothing! Infrastructure is Everything!

Let’s start by looking at this clever map of the most well-funded AI startups in each state. Upon tallying the results, you’ll note that 21% of the most well-funded AI startups across the US focus exclusively on healthcare. Wow!

Healthcare is, by far, the leading vertical focus for these AI startups, with the next largest focus being Business Intelligence (BI) @ 12%, followed by Cybersecurity and Marketing, both @ 9%. Interesting. This does, indeed, feed the bullishness. And, it’s not too hard to make the leap that while the Cybersecurity fellows are horizontally focused, they are going to help our industry, too!

Next, let’s look at a very clever application of Machine Learning in healthcare. Ayasdi, whose tagline is Use machine intelligence to become an automated, data and compute driven enterprise, has partnered with Mercy to optimize clinical pathways (read about it here). Using Ayasdi, Mercy was able to identify that the administration of a specific analgesic after arthroscopic knee replacement surgery correlated with lower costs and shorter hospital stays. Woah! Expanding this sort of next-generation, new-stack application opens up a multitude of possibilities. As Seth Barbanell, MD, Vice President of Mercy’s Clinical Performance Acceleration says, “Ayasdi will help us deliver new care pathways that provide improved clinical outcomes, such as higher patient satisfaction, lower readmissions, shorter length-of-stays, and lower costs. Additionally, Ayasdi will enable Mercy to maintain and optimize these care pathways on a frequent basis as industry conditions change.” Yes! Better patient care! Better patient outcomes! Higher patient satisfaction! Lower costs!

Read the source article at blog.purestorage.com.