IBM Watson Health says AI for clinical decision support is making progress
Tech giant IBM showed off the results of a series of studies indicating Watson Health, the company’s division dedicated to data-driven health technologies, has made progress in providing clinical decision support for cancer care.
WHY IT MATTERS
The study results come as IBM Watson Health has been making major investments in health AI — such as the
$50 million it gave to Brigham and Women’s and Vanderbilt to help to advance the science of AI and its application to major public health issues — and as the company faces increased scrutiny for under delivering and struggling sales for its drug discovery AI services, among other issues.
HOW IT WORKS
The Watson Health cognitive computing cloud platform can analyze large volumes of patient healthcare data using embedded artificial intelligence and machine learning technology.
Among the 22 studies the company showcased at the American Society for Clinical Oncology was a trial where Watson for Oncology was shown to inform clinical decision changes in 13.6 percent of cases at a hospital in India.
In the cases where decisions were changed, Watson was able to provide evidence for newer treatments, more personalized alternatives, or new insights from genotypic and phenotypic data.
"We consider Watson for Oncology to be an important tool to support decision making, and this study suggests that AI could help reduce variability of care," lead investigator SP Somashekhar, chairman of surgical oncology at Manipal Hospitals, said in a statement.
In another study, Watson for Genomics was found to identify clinically actionable genomic variants that had not been identified in manual interpretation in a third of patients at a hospital in South Korea.
ON THE RECORD
"AI is helping multidisciplinary tumor boards make more informed decisions based on curated scientific evidence and it is helping to improve patient satisfaction by delivering a comprehensive view of treatment options," Nathan Levitan, chief medical officer for oncology and genomics at IBM Watson Health, said in a statement.
Meanwhile, physicians from Beijing Chaoyang Integrative Medicine Emergency Medical Center’s oncology department reported improved levels of patient engagement after incorporating Watson for Oncology into the consultation process.
Overall, machine learning can be used to automatically identify relevant clinical publications from biographic databases, without relying on expert curation or bibliometric methods.
The use of machine learning to identify relevant publications could help reduce the time clinicians spend finding important and relevant evidence for a patient.
Watson Health was created to help address pressing health challenges through data, analytics and AI, and the platform also provides tailoring offerings to support the workflow experience of oncologists, based on feedback from physicians and insight from scientific data.
"Patients often face grueling and confusing treatment regimens, while oncologists sift through reams of medical literature and genomic data to identify the best care plan for each individual patient,” Levitan said. “All the while, researchers are hamstrung by trials that too often fail due to low patient recruitment."
Nathan Eddy is a healthcare and technology freelancer based in Berlin.
Email the writer: firstname.lastname@example.org