SON Faculty Publish Study On Predicting Cancer Patients’ Symptoms

Chris Miaskowski

As part of a research collaboration, a SON team has published a study that is the first to use two machine learning techniques to accurately predict the severity of three common and inter-related symptoms in cancer patients: anxiety, depression and sleep disturbance.

The paper Learning From Data To Predict Future Symptoms of Oncology Patients, which published in the PLOS ONE journal, was a collaboration between the University of Surrey and UCSF. The UCSF research was led by Professor Christine Miaskowski in Physiological Nursing, and the team included Bruce Cooper, Xiao Hu, Kord Kober, Jon Levine and Steven Paul.