The study’s lead author, Dr. S.P. Somashekhar, chairman of the Manipal Comprehensive Cancer Center of Manipal Hospitals, in Bengaluru, India, told the audience at the meeting that the study found that the oncologists agreed with WFO about REC and FC recommendations 90 percent of the time.

The type — and complexity — of cancer impacted the rate of agreement. For non-metastatic disease, doctors and machine agreed 80 percent of the time. When metastases occurred, however, agreement was just 45 percent. WFO and physicians concurred in cases of triple-negative breast cancer 68 percent of the time.


More recently, a regional facility in South Florida became the first community medical center in the U.S. to adopt the cognitive computing platform in an effort to boost outcomes of patients afflicted with cancer.

“IBM’s technology, Watson for Oncology, will be provided to oncologists at Jupiter Medical Center to help doctors make personalized, evidence-based treatment decisions for their patients,” Dr. Andrew Norden, deputy chief health officer, IBM Watson Health, told HCB News. “For IBM, this is an important milestone, as it is the first adoption of Watson for Oncology to support community oncologists in the U.S.”

The advances in AI-based medical care are coming rapidly, and the roll-out has begun. “Deep learning is a truly transformative technology, and the longer-term impact on the radiology market should not be underestimated,” advised Signify's Harris. “It’s more a question of when, not if, machine learning will be routinely used in imaging diagnosis.”

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