Editorial: “Mr. Watson, Come Here!”

How Artificial Intelligence is Revolutionizing Healthcare!

“Mr. Watson, come here.” These immortal words uttered by Alexander Graham Bell on March 10, 1876 ushered in a new era in communication technology. Fast forward to May 1997 when another seminal technological event occurred: IBM’s Deep Blue defeated the world’s chess champion, Mr. Garry Kasparov, in a rematch by the score of 3-½ to 2-½. This was the first time a computer program had defeated a reigning world chess champion under tournament conditions. The results sent a tremor through the chess world, and even more importantly, through the artificial intelligence universe. If machines could beat the chess champ, what else could they accomplish?

Even though IBM retired Deep Blue after the match, much to the chagrin of Mr. Kasparov, the world did not need to wait very long for the next surprise development. In 2011, IBM’s Watson, named after the firm’s first CEO Thomas J. Watson, defeated the two winningest human players on the game show Jeopardy in an exhibition match. Together the two human players had amassed over $5 million in prize money. Unlike the previous chess match, this event occurred before millions of viewers. The artificial gene was now out of the bottle. Had Watson, in effect, passed the Turing test? Alan Turing, the mastermind behind breaking the German’s Enigma code during World War II, had proposed the test in the early 1950s. The test would be passed if a human could not differentiate between the responses to a series of questions from a machine or another human. Passing the test suggested that the machine was capable of cognition.

The IBM Watson team did not rest on their winning laurels very long. They identified the healthcare industry, which represents approximately one-seventh of the United States economy, as a market opportunity with tremendous potential. One of their first applications was providing lung cancer diagnostics and treatment planning at the Memorial Sloan-Kettering Cancer Center. As it turns out, nearly one in twenty patients are misdiagnosed by the treating physician. This statistic should not be too surprising given the fact that at least a dozen new diseases have been identified over the past two decades, such as Hantavirus Pulmonary Syndrome. Furthermore, the variety and volume of drug prescriptions consumed by many patients can further mask the true problems, which can then lead to ineffectual treatment.

Watson is already capable of storing far more medical information than doctors, and unlike humans, its decisions are all evidence-based and free of cognitive biases and overconfidence. It’s also capable of understanding natural language, generating hypotheses, evaluating the strength of those hypotheses, and learning—not just storing data, but finding meaning in it.—Lauren F. Friedman[1]

8609 smIBM is not the only player applying artificial intelligence (AI) to the healthcare industry. Virtual health assistances are being deployed to better ensure that patients take their medications on the prescribed schedule. These systems can engage in a conversation with the patients regarding their current health status and motivation regarding their drug therapy. The resultant data can be sent to the patients’ primary health care physician. Several big pharma firms are also combining artificial intelligence and big data to identify new drug compounds. Historically, it takes ten years and billions of dollars to bring a new drug to the marketplace. An AI-based approach could significantly reduce both of these estimates.

A hospital bed is a parked taxi with the meter running.Groucho Marx

Nevertheless, many challenges remain in this brave new AI world of healthcare. One is the task of gaining access to high-quality patient, drug and epidemiology data. Presently, most patient medical records are not available on the cloud. Some pundits argue that this is actually a good thing given the recent hacker security scandals. Another assignment involves the development and training of AI-based models, which can be used for pattern recognition, diagnostics and prescriptive assessments. There is also the philosophical question regarding the future role of doctors: Could they become obsolete as the technology continues to improve? The key to the long-term survival of human doctors is to learn how to most effectively work with systems like Mr. Watson! Along those lines, imagine your next visit to the doctor’s office, where you are greeted by a human-looking robot (i.e., android) at the front desk. After your appointment and, of course, payment are digitally processed, you are escorted by another robot to the exam room. Presently your doctor arrives and after exchanging pleasantries, he calls out, “Mr. Watson, come here.” In a flash, a strange-looking contraption appears, perhaps resembling R2D2. Within a minute or so, the device has processes your entire medical history along with an assessment of your medication and described symptoms. At that point, the robot then provides the doctor with a diagnosis and a prescribed course of action. This is the future of healthcare and it is coming soon to a doctor’s office near you!

Always laugh when you can. It is cheap medicine.Lord Byron

 

[1] Friedman, Lauren F. (April 22, 2014). “IBM’s Watson Supercomputer May Soon Be The Best Doctor In The World,” Business Insider. http://www.businessinsider.com/ibms-watson-may-soon-be-the-best-doctor-in-the-world-2014-4#ixzz2zd8LJGGk

Author of the article
Owen P. Hall, Jr., PE, PhD
Owen P. Hall, Jr., PE, PhD,

, holds the Julian Virtue Professorship and is a Rothschild Applied Research Fellow. He is a Professor of Decision Sciences at Pepperdine University’s Graziado School of Business and Management. He has more than 35 years of academic and industry experience in mobile learning technologies and business analytics.

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