November 22, 2016 / All Stories

Need to win Jeopardy and conquer cancer? Call Watson

The global burden of cancer is expected to grow over the next 15 years. Can artificial intelligence help tackle the complexities of the disease?

Image provided by IBM Watson

From self-driving cars to bionic arms, the dreams of artificial intelligence (AI) once imagined in science fiction novels are now reality.

But can AI tackle the complexities of diseases like cancer?

According to the International Agency for Research on Cancer (IARC), by 2030, the global burden of cancer is expected to grow to an estimated 21.7 million new cancer cases and 13 million cancer deaths because of the growth and aging of the population.

“To treat cancer more efficiently, we need to see patterns that we didn’t see before. I think that now we have digital tools that can enable us to do that,” says Ketil Widerberg, general manager, Oslo Cancer Cluster, an oncology research and industry cluster in Norway dedicated to accelerating the development of new cancer diagnostics and medicines.

As individual and population-health data grow – doubling about every 24 months – the ability to make sense of it and take action is limited for health care practitioners.

To keep up, doctors would have to read 29 hours each workday to understand the latest research and advances. And, as researchers uncover new findings about the origins and mutations of cancer, treatment approaches can vary down to the individual.

Now, we’re turning to the most successful player of Jeopardy!, a popular American television game show, to help reverse the course of the deadliest disease of all time.

Paging Dr. Watson

While IBM Watson is most famous for cruising to an easy victory on the popular U.S. quiz show in 2011, the artificial intelligence platform has not been idle since then.

IBM launched Watson Health in 2015, which, in part, aims to tackle some of the toughest challenges of cancer diagnosis and treatment.

Memorial Sloan Kettering, a famous cancer hospital in the United States, and IBM have been training Watson for Oncology in reading and understanding the oncology domain. Watson for Oncology is a specialized computing system within Watson Health designed to help the entire physician community when they consider cancer treatment options.

Watson for Oncology draws from an impressive corpus of information, including curated literature and rationales, as well as more than 290 medical journals, more than 200 textbooks and 12 million pages of text. Watson ranks identified treatment options and provides links to supporting evidence for each option to help oncologists as they consider treatment options for their patient.

No human being can keep up with the enormous amount of published literature – but Watson can by reading millions of pages in just seconds, according to Peter Mortensen, Watson Health executive, the Nordic Region.

The homework seems to have paid off.

In one study at the University of North Carolina School of Medicine, Watson matched 99 percent of the treatment recommendations made by oncologists; and in 30 percent of the cases, Watson identified additional options that the doctors missed.

Image provided by IBM Watson

Cancer collaboration in action

In Norway, IBM teamed up with the Oslo Cancer Cluster and its members, including AbbVie, to work toward the organization’s mission to accelerate the development of new cancer diagnostics and medicines.

The group is nearing the opening of an innovation center where researchers and partners can interact with technologies like Watson to identify gaps in oncology research.

Currently, IBM Norway is involved in projects with the Norwegian Research Council ICC Light House Project called BIGMED, focused on four medical areas: colon cancer with liver metastasis, lung cancer, sudden cardiac death and monogenic diseases.

The goal is to create a decision-support platform that makes sense of unstructured data combined with genomic data and is presented to clinicians for medical decisions, focusing on precision medicine.

“As we develop this project, we will begin to understand genome variations and understand unstructured data from electronic medical records to do analytics and come up with information or knowledge that can be presented to the clinician for medical decisions,” says Loek Vredenberg, CTO and technical leader, IBM Norway.
With projects like BIGMED and others all over the world, the hope for significant improvements to accelerate cancer diagnoses and determine the right course of treatment has never been greater.   

“If we speak boldly about the abilities of new health data and the research and cognitive tools they have, then I think the goal is to diagnose early enough to intervene and treat, ultimately making  cancer a chronic disease,” Widerberg says.

Vredenberg adds, “Our hope is the technology brings to bear all knowledge we have about cancer for each and every patient in the world, irrespective where they are, the doctor treating them, the institution; that this knowledge is available to all doctors anywhere … It’s a very ambitious goal and this will take time, but we are making good strides in the right direction.”

As a member of the Oslo Cancer Cluster, AbbVie sponsored “Behind the Scenes of Breakthrough Innovations” in September 2016, featuring the work of Oslo Cancer Cluster and IBM Watson Health.

Five ways AI is used in health care

In addition to cancer research, doctors, scientists and health care professionals are using artificial intelligence in other ways to improve public health. Five ways AI is already making an impact:

1. Restoring the senses.

One man experienced the sense of touch for the first time since 2004 with his mind-controlled robotic arm.

2. Diagnosing Alzheimer’s disease.

In one study, researchers applied AI algorithms to MRI brain scans to classify Alzheimer’s disease and various forms of dementia.

3. Identifying deadly infections earlier.

Sepsis, a deadly infection if left undetected or treated too late, can be caught with the Targeted Real-Time Early Warning System (TREWScore), a real-time early warning score that predicts in advance which patients are at risk for septic shock.

4. Clinic visits … with your phone.

Backed by AI, some smartphone apps can take your personal history, ask questions about symptoms, make treatment recommendations and follow up.

5. Trying on new genes.

With greater computer power comes the ability to analyze vast sets of genetic information, medical records and DNA to better understand how to identify and treat disease.

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