Machine learning finds combined biological and psychosocial data improve chronic pain prediction

Researchers at McGill University and other institutes recently carried out a study aimed at identifying biomarkers and psychosocial factors associated with the development of chronic pain conditions. Their findings, published in Nature Human Behavior, were obtained by analyzing data from a large biomedical database, namely the UK Biobank, using advanced machine learning techniques.

“Our study started as an effort to identify reliable brain-based biomarkers for chronic pain using data from the UK Biobank, the largest brain imaging cohort available,” Matt Fillingim, first author of the paper, told Medical Xpress. “We quickly found that these biomarkers could not reliably distinguish chronic pain from pain-free individuals.

“However, when applied to specific pain conditions like fibromyalgia and rheumatoid arthritis, the biomarkers showed greater promise, prompting us to integrate additional psychosocial factors and diverse biological data (blood tests, bone imaging, genetics) to better understand chronic pain and its associated conditions.”

Sign up for Blog Updates