By: Stephen C. Webster
An artificial intelligence
system developed by researchers at Indiana University can diagnose
illnesses and prescribe courses of treatment significantly better than a
human doctor, the university said Monday.
Using a computerized decision making processes similar to IBM’s wiz computer “Watson” that won the game show “Jeopardy,”
researchers plugged in big medical data sources and tasked it to
simulate treatment outcomes for 500 patients, most of whom suffered from
clinical depression and at least one other chronic condition, like high
blood pressure or diabetes.
Using data from actual
patient-doctor treatment sessions, computer science assistant professor
Kris Hauser and Ph.D. student Casey C. Bennett compared real-life
outcomes to simulated treatment regiments and found their computer was
nearly 42 percent better at diagnosing illnesses and prescribing
effective treatments than human doctors.
Better still, researchers said
the accuracy in diagnosis and treatment could reduce health care costs
by getting it right the first time. Bennett and Hauser’s models said
their computer diagnosis would have provided a 58.5 percent cost savings
“per unit of health outcome” versus treatment as usual by a doctor.
While the research is
exciting, Bennett and Hauser have some serious competition on the
horizon. IBM’s own “Watson” was recently tasked to work with health
insurer WellPoint and the Memorial Sloan-Kettering Cancer Center in New
York to improve treatment outcomes for cancer patients.
One day soon, doctors may even rely upon computers of this sort to
model alternative diagnoses and treatment options, giving patients more
choice and reliability in health care.
In other words, big data’s emergence in consumer medicine is just beginning.
“Even with the development of
new AI techniques that can approximate or even surpass human
decision-making performance, we believe that the most effective
long-term path could be combining artificial intelligence with human
clinicians,” Bennett said in an advisory. “Let humans do what they do well, and let machines do what they do well. In the end, we may maximize the potential of both.”
The research appears in the March 2012 edition of Artificial Intelligence in Medicine.
——
——
Photo: Shutterstock.com.
No comments:
Post a Comment