IBM Watson Health funds AI research at Brigham and Women’s, VUMC
IBM Watson Health aims to jump-start efforts at healthcare organizations to advance the use of artificial intelligence on public health issues.
On Wednesday, the AI branch of IBM announced plans for a 10-year, $50 million investment in research and collaborations with two academic medical centers—Brigham and Women’s Hospital in Boston and Vanderbilt University Medical Center, Nashville, Tenn.
The organizations say the initiatives will focus on “critical health problems that are ideally suited for AI solutions.” Early efforts will seek to improve the utility of electronic health records and claims data to address public health issues such as patient safety, precision medicine and health equity.
The research will also look at physician and patient experience and interactions with AI technologies.
“Physicians are spending an average of two hours with their electronic health records and deskwork for every hour of patient care, a phenomenon the American Medical Association says is leading to a steady increase in physician burnout,” says Kyu Rhee, MD, vice president and chief health officer at IBM Watson Health. “AI is the most powerful technology we have today to tackle issues like this one, but there is still a great deal of work to be done to demystify the real role of AI in healthcare with practical, proven results and clear-cut best practices.”
The initiative will involve David Bates, MD, chief of general internal medicine at Brigham and Women’s Hospital, as well as Kevin Johnson, MD, chair of the department of biomedical informatics at Vanderbilt University Medical Center, and Gordon Bernard, MD, executive vice president for research for the facility.
Additionally, IBM Watson Health and the Broad Institute of MIT and Harvard are expanding their partnership to help clinicians better predict the possibility of serious cardiovascular diseases. By working with genomics, clinical data and AI, IBM and the Broad Institute hope this three-year project will help provide doctors with tools to tap into the potential of genomics data and better understand the intrinsic possibility an individual has for a certain disease.
This initiative will incorporate population-based and hospital-based biobank data, genomic information and electronic health records to build upon and expand the predictive power of polygenic scoring, otherwise known as genetic risk scoring. IBM and the Broad Institute are aiming to build algorithms that can pinpoint and learn from trends in these data points, and then indicate a potential predisposition to certain health conditions.
Ultimately, this AI technology will aim to produce models which bring together and analyze a multitude of genetic risk factors within an individual’s genome, along with existing health records and biomarkers, to help clinicians more accurately predict the onset of complex and often fatal conditions in patients. IBM Watson Health and the Broad Institute announced a five year initiative in 2016 to help researchers use machine learning and genomics to better understand why and how cancers become resistant to therapies.