Paging Dr. Robot: IBM Introduces the Clinician’s Trusty Sidekick, Watson

IBM's Watson brings a whole new dimension to health care by integrating thousands of sources of literature and data into a comprehensive evaluation of a given patient. (Wikimedia Commons user Clockready / Wikimedia Commons)
IBM’s Watson brings a whole new dimension to health care by integrating thousands of sources of literature and data into a comprehensive evaluation of a given patient. (Wikimedia Commons user Clockready / Wikimedia Commons)

Keeping up with medical research is a monstrous task for today’s clinicians. Masses of new data rapidly augment the already-enormous collection of medical knowledge, and already-busy doctors struggle to constantly self-educate. Is it possible for doctors to be as informed as they could and should be? Will we tragically fall victim to the crippling amounts of data we produce? Are we doomed to be under-informed for all of eternity? The answer, according to the latest technology, is no! Have no fear, IBM’s Watson is here!

Watson didn’t actually start as a medical tool. This technology, first put to work in 2011 to defeat top Jeopardy! players, simply excels at information processing. Watson is special; not only does it comb through extensive data, but it also searches using human-like technqiues. This means that Watson employs natural language processing, giving it the ability to understand context, subtle meanings, and figurative or ambiguous language – all things that other information processors struggle with. Watson is also able to generate and evaluate hypotheses, learning and adapting with every interaction. IBM posits that Watson is valuable beyond dominating game shows, and is promoting  it as a tool that could be used to process patterns of financial information, engage and interact personally with consumers, and serve healthcare workers by recommending diagnoses and treatments.

When working with Watson, doctors can input all the available medical information on a given patient, including family history, current medications, and co-morbid conditions. Watson then rigorously searches uploaded literature for relevant information using DeepQA software and outputs a list of possible diagnoses in rank order. It also recommends treatments, listing the pros and cons associated with each technique. In this way, Watson acts as an artificial doctor that has the superpower of accessing and processing all information relating to the patient’s status, including doctors’ and nurses’ notes on similar cases, and coming to an evidence-based conclusion. This task that would not only take a medical professional a long time, but would also require him or her to be omniscient. A patient in a hospital assisted by Watson benefits from his or her own doctor’s clinical experience as well as all other doctors’ uploaded clinical experiences. This is especially important in cases of unknown diseases or those without established treatment protocols. A recent partnership with the renowned Memorial Sloan-Kettering Cancer Center in New York City has integrated Watson’s services into the fight against cancer. Read about the process of training Watson to serve the medical community here.

Watson certainly seems like an asset to the healthcare field. For a discipline swimming in data, it could capitalize on available information and help clinicians arrive at previously inaccessible answers. However, if the brainstorming and problem-solving aspect of healthcare is outsourced to Watson, where would that leave doctors? Watson may allow doctors to spend more time with patients – an advantage that could indirectly improve health outcomes. This technology could also change the function (and value) of medical school. Could Watson render doctors obsolete? Possibly. Even if the impact of Watson on the structure of health care is not this extreme, its presence will likely shift the dynamics of diagnostics and treatment planning in many areas of medicine and will have interesting financial, legal, and social ramifications.

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