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On Cancer: Memorial Sloan Kettering Trains IBM Watson to Help Doctors Make Better Cancer Treatment Choices

By Jennifer Bassett, MA, Writer/Editor  |  Friday, April 11, 2014

A team of physicians and analysts at Memorial Sloan Kettering has been “training” IBM Watson for more than a year to develop a tool that can help medical professionals choose the best treatment plans for individual cancer patients.


When you watch this year’s Masters golf tournament, you may notice a Memorial Sloan Kettering oncologist featured in a new IBM TV spot, which IBM's Jon Iwata discusses here.  As you already may have seen on CBS This Morning or read in recent articles, such as Mark G. Kris’s piece in The Atlantic, some of our oncologists have spent the last year training IBM’s Watson to help personalize cancer care.

What Is Watson?

For those who don’t know, IBM Watson™ (made famous by its Jeopardy! win) is a powerful cognitive technology developed by IBM that processes information more like a human than a computer, by understanding natural language, generating hypotheses based on evidence, and learning as it goes. But beyond Jeopardy!, what if Watson’s power could also be used for the greater good, to help medical professionals choose treatment options for cancers?

Cancer is not one disease but a cluster of diseases with hundreds of subtypes, each with a different genetic fingerprint. Although significant discoveries have delivered extraordinary insights into cancer biology and strategies for targeting specific molecular alterations in tumors, these advances have also increased the complexity of treating individual patients. Vast amounts of rapidly changing information means it can take years for the latest developments in oncology to become standard care across all communities.

Why Watson and Memorial Sloan Kettering

When utilizing Memorial Sloan Kettering’s unmatched breadth and depth of experience, gained from treating more than 30,000 patients with cancer every year, Watson will take information about a specific patient and match it to a huge knowledge base incorporating published literature and the treatment history of similar patients. Watson’s ability to mine massive quantities of data means that it can also keep up — at record speeds — with the latest medical breakthroughs reported in scientific journals and medical meetings. Additionally, because it utilizes cognitive computing, Watson continually “learns,” thereby improving its accuracy and confidence in the treatment options it suggests.

Memorial Sloan Kettering clinicians and analysts have been hard at work training Watson to extract and interpret physician notes, lab results, and clinical research. (All identifying patient information is removed prior to beginning the process.) Memorial Sloan Kettering’s expertise and experience with thousands of patients are the basis for teaching Watson how to translate data into actionable clinical practice based on a patient’s unique cancer. While initially focused only on breast and lung cancers, the work has expanded to more than a dozen other common solid and blood cancers such as colon, prostate, bladder, ovarian, cervical, pancreas, kidney, liver, and uterine, as well as melanomas and lymphomas.

How the Tool Can Work

Infographic: Advancing the Future of Personalized Cancer Care Enlarge Image Infographic: Advancing the Future of Personalized Cancer Care The tool — currently in development — is designed to help oncologists anywhere make the best treatment decisions for their individual patients. It learns to prompt physicians if missing information is needed to determine an initial set of treatment options. The goal is to display several choices for the physician with various degrees of confidence and to provide supporting evidence from guidelines, published research, and Memorial Sloan Kettering’s breadth of knowledge.

The Impact

By combining Memorial Sloan Kettering’s world-renowned cancer expertise with the analytical speed of IBM Watson, the tool has the potential to transform how doctors provide individualized cancer treatment plans and to help improve patient outcomes. Oncologists anywhere will be able to make more specific and nuanced treatment decisions more quickly, based on the latest data.

The tool also has the potential to help transform clinical research by allowing doctors to match patients to clinical trials, as well as gather additional data to prompt new research opportunities. Additionally, it can be used to reduce variation in cancer care, decrease the time it takes for the latest research to enter clinical practice, increase adherence to evidence-based medicine, as well as share the wisdom and knowledge of Memorial Sloan Kettering’s expert clinicians.

Watch the video above to learn more about Memorial Sloan Kettering’s collaboration with IBM Watson. Keep a lookout for IBM’s new ad campaign and more updates from Memorial Sloan Kettering on our partnership with IBM Watson.


I am 12 yrs. out from an Autogolous Transplant for B-cell NHL. So far so good.
Hope that the "success stories" from the previous years patients are included in the data that Watson will have. Certainly this will add to the informed decisions that are to be made. Thank you for these "updates". June Fay

I just posted comments, can't find where
Stating my mothers cancer is sc lung cancer
Correction it is non sc lung cancer. I like to be directed to where my initial comment can be found. Thank u

Diane, your original comment was made on a different post about IBM Watson. You can find it here: Thanks for your interest in Memorial Sloan Kettering.

I author a nurses blog on the Microsoft in Health website. I am always eager to see the work of Watson and Sloan Kettering. Can I include a link and mention this article in an upcoming posting? Thanks!

Amy, we would be happy to have you highlight this story by linking to it in your nurses blog. Thank you for your comment.

You are training your replacement. Bill Brody at Hopkins remarked recently that radiologists are on the cusp of obsolescence as software detection programs improve. You're helping to show that medical specialties will be next. Sure, "caring" is important, but nurses and others on the cancer care team do more of that than the physician, and given the popularity/reputation of academic cancer centers, there is a big market for treatment centers where caring is trumped by effectiveness. A national network of Watsons capable of staying up to date on the latest cancer evidence in every sub-specialty, would be capable of real-time translational research, would know all of the best decisions to make at each juncture on the best pathways, would know the effectiveness of the best specialists for subsequent referrals, would always be on call, wouldn't mistreat staff, wouldn't balk at evening/weekend hours, would promptly communicate with primary care, and would have a frame of reference for treatment decisions that is exponentially more significant than a string of anecdotes over a single career. The list goes on, but as it becomes evident that high quality cancer care comes from standardization of practice towards best evidence, computers will soon be most effective at both assessing the evidence and the patient and optimizing their treatment to both.

Hi, I am from Australia. I am pretty excited by the potential of this technology to influence cancer care here. How close is Watson to going live? Is there interest in taking it internationally? Need trial sites :-) ?
Congratulations on such a potentially ground breaking innovation.

Dear Sonia, thanks so much for your interest. We're not directly involved in the implementation of Watson at healthcare institutions -- our role has been to "train" Watson. However, we can tell you that there are plans to use Watson at Bumrungrad International Hospital, in Bangkok, Thailand. You can read more about the project here:

Is there anywhere I can have a look at a dummy/trial interface for cancer care?
Thanks! sonia

Dear Sonia, this IBM Watson demo on cancer diagnosis and treatment, which is on YouTube, may be useful and of interest:

Thank you for your comment.

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