New AI models used to predict cancer patients' mental health

Researchers at the University of Surrey have collaborated with the University of California to develop two machine learning models to predict the severity of depression, anxiety and sleep disturbance in cancer patients


Researchers at the University of Surrey, in collaboration with the University of California, have developed a technique using machine learning technology to predict the severity of three common psychological symptoms cancer patients experience to enhance their quality of life.

At the University of Surrey, researchers led by Payam Barnaghi, professor of machine learning intelligence, from the Center for Vision, Speech and Signal Processing (CVSSP) have created two machine learning models that are able "to accurately predict the severity of three common symptoms faced by cancer patients – depression, anxiety and sleep disturbance".

"All three symptoms are associated with severe reduction in cancer patients' quality of life," the report added.

To develop the models, the researchers analyzed existing data comprising of symptoms cancer patients experienced during computed tomography x-ray treatments.

The machine learning technique can assist clinicians identify high-risk patients, support patients' in symptom experience and create tactical treatment plans.

CVSSP director, Adrian Hilton said: "These exciting developments by Professor Barnaghi and his team show the incredible potential of machine learning in transforming the way healthcare professionals treat people suffering from cancer.

"We continue to explore the boundless potential of AI at CVSSP and we believe our work has a real place in helping to shape the future of health services across the globe."

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