A new study suggested that two machine learning (ML) models Support Vector Regression (SVR) and Non-linear Canonical Correlation Analysis by Neural Networks (n-CCA) are able to predict the severity of three common symptoms faced by cancer patients such as depression, anxiety and sleep disturbance. The researchers believe that these type of models can be used to identify high-risk patients, educate them about the symptom and the experience. It can also improve the timing of preemptive and personalised symptom management interventions. Researchers from the University of Surrey in UK said that these three symptoms are associated with a severe reduction in cancer patients' quality of life. In addition, Professor from the varsity, Payam Barnaghi said, "These exciting results show that there is an opportunity for machine learning techniques to make a real difference in the lives of people living with cancer."