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SmartData Collective > Business Intelligence > Dr. House, the computer?
Business Intelligence

Dr. House, the computer?

StephenBaker1
StephenBaker1
4 Min Read
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One of the most important of my book chapters, which I will write this month, grapples with the prospects for question-answering computers in the business world. The idea is that Watson, the Jeopardy-playing computer, will spawn smaller and cheaper specialists, which will sift through mountains of data, make correlations and answer questions in specific industries.

One of the most important of my book chapters, which I will write this month, grapples with the prospects for question-answering computers in the business world. The idea is that Watson, the Jeopardy-playing computer, will spawn smaller and cheaper specialists, which will sift through mountains of data, make correlations and answer questions in specific industries.

One of the most promising is medicine. Dr. Robert Wachter of the U.California San Francisco Dept. of Medicine, writes about the diagnostic possibilities for computers in a thoughtful and well-documented post.

He writes:

With Watson-like programs, we may finally be on the cusp of having computer systems that will at least do the first step very well: taking an initial fact set and using it to answer a clinical question or create a differential diagnosis list. (There are early medical versions of this model; the best known is called Isabel, and some of its early results are relatively promising. But none have anywhere near Watson…rsquo;s computerized firepower.) The other steps might prove to be easier …ndash; a …ldquo;Watson MD…rdquo; could surely …ldquo;know…rdquo; the test characteristics of the most common medical studies, and easily apply the Bayesian algorithm to these results.

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Finally, the next generation of medical AI computers will ultimately …ldquo;learn…rdquo; from their experience. Once every patient…rsquo;s data is stored in the computer and the final, correct answer is also captured by the system, the AI program need not rely only on textbook chapters and articles as its source of data. Instead, it could learn that patients like the one you are seeing ultimately turned out to have Wegener…rsquo;s granulomatosis, even though they were frequently mistakenly diagnosed initially as having atypical pneumonia or sinusitis. And it could adjust its algorithm accordingly. This, of course, is analogous to Amazon.com…rsquo;s magical feat of informing us that …ldquo;customers like you bought X book….rdquo; Except it would be …ldquo;patients like yours had Y disease….rdquo;

***

I spent most of the last two weeks writing. I sent the first eight (of 12) chapters of the book to my editor on Thursday, and then went back to IBM labs yesterday to watch Watson in yet more sparring sessions with humans. IBM is working with a number of universities on this project, including MIT, Carnegie Mellon, USC, U Texas, and others. They had about 30 of the academics there yesterday. They were in an auditorium watching the competition on the big screen. It might have seemed weird to an outsider to see all these people cheering for a computer over fellow humans. But really, they were cheering for themselves, and what they had helped to build.

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