Washington, Sept 14 (ANI): The need for a better way to objectively measure the presence or absence of pain instead of relying on patient self-reporting has long been an elusive goal in medicine.
But now, using advances in neuroimaging techniques, researchers including one of Indian-origin from the Stanford University School of Medicine trained a computer algorithm to interpret magnetic resonance imaging (MRI) data of the brain and determine whether someone is in pain.
Researchers took eight subjects, and put them in the brain-scanning machine. A heat probe was then applied to their forearms, causing moderate pain. The brain patterns both with and without pain were then recorded and interpreted by advanced computer algorithms to create a model of what pain looks like. The process was repeated with a second group of eight subjects.
The idea was to train a linear support vector machine - a computer algorithm invented in 1995 - on one set of individuals, and then use that computer model to accurately classify pain in a completely new set of individuals.
The computer was then asked to consider the brain scans of eight new subjects and determine whether they had thermal pain.
"We asked the computer to come up with what it thinks pain looks like," said Neil Chatterjee, currently a MD/PhD student at Northwestern University.
"Then we could measure how well the computer did." And it did amazingly well. The computer was successful 81 percent of the time.
The study was recently published in the online journal PLoS ONE. (ANI)
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