MIT’s robot was designed to learn from nurses working in a labor unit. The robot was then able to make scheduling recommendations like assigning patients to labor beds and assigning nurses to assist with C-sections. These recommendations were accepted by nurses and physicians 90 percent of the time.
In hospitals, robots currently assist in simple tasks like delivering supplies and medications, but they require explicit instructions and are often incapable of predicting human needs.
“The aim of the work was to develop artificial intelligence that can learn from people about how the labor and delivery unit works, so that robots can better anticipate how to be helpful or when to stay out of the way — and maybe even help by collaborating in making challenging decisions,” said MIT professor Julie Shah, PhD, the senior author of the paper. “The awkward robots of the past will be replaced by valued team members.”
More articles on health IT:
IT jobs grow in June, but development remains slow
ONC launches challenge seeking input on using blockchain in health IT
Why 55% of health IT professionals are constantly stressed: 7 survey findings
At the Becker's 11th Annual IT + Revenue Cycle Conference: The Future of AI & Digital Health, taking place September 14–17 in Chicago, healthcare executives and digital leaders from across the country will come together to explore how AI, interoperability, cybersecurity, and revenue cycle innovation are transforming care delivery, strengthening financial performance, and driving the next era of digital health. Apply for complimentary registration now.