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William Vorhies's Blog Posts Tagged 'healthcare' (7)

Predictability of Life Outcomes - Guess We Can’t Predict Everything

Summary: Whether trying to predict the life outcomes of disadvantaged kids or to model where ventilators will be most needed, a little humility is in order.  As this study shows, the best data and the broadest teams failed at critical predictions.  Getting the model wrong, or more importantly using it in the wrong way can hurt all of us.

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Added by William Vorhies on April 6, 2020 at 2:56pm — No Comments

Building a COVID-19 Vulnerability Index

Summary: Since COVID-19 is occupying most of our thoughts these days, it seems appropriate to highlight where AI/ML is making a contribution to getting us out of our homes and back to work. 

 

Since COVID-19 is occupying most of our thoughts these days, it seems appropriate to highlight where AI/ML is making a…

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Added by William Vorhies on March 24, 2020 at 8:40am — 2 Comments

The Next Big Thing in AI/ML is…

Summary:  AI/ML itself is the next big thing for many fields if you’re on the outside looking in.  But if you’re a data scientist it’s possible to see those advancements that will propel AI/ML to its next phase of utility.

 

“The Next Big Thing in AI/ML is…” as the lead to an article is probably the most…

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Added by William Vorhies on October 21, 2019 at 9:18am — 1 Comment

Doctors are from Venus, Data Scientists from Mars – or Why AI/ML is Moving so Slowly in Healthcare

Summary: The world of healthcare may look like the most fertile field for AI/ML apps but in practice it’s fraught with barriers.  These range from cultural differences, to the failure of developers to really understand the environment they are trying to enhance, to regulatory and logical Catch 22s that work against adoption.  Part 3 of 3.

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Added by William Vorhies on January 21, 2019 at 7:59am — 2 Comments

The AI/ML Opportunity Landscape in Healthcare. Do It Right or It Will be More of a Mine Field.

Summary:  Despite hundreds of projects and thousands of data scientists devoted to bringing AI/ML to healthcare, adoption remains low and slow.  A good portion of this problem is our own fault for failing to see the processes being disrupted through the eyes of the physician users.  Here we lay out the healthcare opportunity landscape but for data scientists following classical disruption strategies, it may be more of a minefield.  Part 2 of…

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Added by William Vorhies on January 14, 2019 at 8:00am — No Comments

Seeing the AI/ML Future in Healthcare Through the Eyes of Physicians. It Doesn’t Look Quite the Way Data Scientists See It.

Summary: If you want to understand the promise of AI/ML in healthcare you need to see it through the eyes of physicians, the ultimate users.  Turns out these folks aren’t the rapid adopters you’d think they’d be and the problem is largely with the way data scientists have tried to implement.  Part 1 of 3.

 

It’s…

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Added by William Vorhies on January 7, 2019 at 8:00am — 4 Comments

Watson – Time to Prune the ML Tree?

Summary:  IBM’s Watson QAM (Question Answering Machine), famous for its 2011 Jeopardy win was supposed to bring huge payoffs in healthcare.  Instead both IBM and its Watson Healthcare customers are rapidly paring back these projects that have largely failed to pay off.  Watson was the first big out-of-the-box commercial application in ML/AI.  Has it become obsolete?

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Added by William Vorhies on August 21, 2018 at 10:51am — No Comments

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