In the first study of its kind, newly AI created by researchers at the University of Surrey can advance treatment for cancer patients by assisting physicians in predicting the symptoms of cancer and the degree of severity throughout the treatment plan. The research, carried out at the University of Surrey’s Centre for Vision, Speech and Signal Processing (CVSSP), explains how two machine learning models are capable of predicting the severity of the most common cancer symptoms faced by patients: depression, anxiety and sleep disturbance.
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All these symptoms contribute to a severe reduction in cancer patients' quality of life. This prompted researchers to analyze existing data of the symptoms experienced by cancer patients during the span of computed tomography x-ray treatment. Specifically, to test if the machine learning algorithms have accurately predicted when and if symptoms surfaced, the researchers utilized different time periods during the analysis of the data.
"I am very excited to see how machine learning and AI can be used to create solutions that have a positive impact on the quality of life and well-being of patients,” says Nikos Papachristou, project designer behind the machine learning algorithms for this project.
Results concluded that the actual recorded symptoms are very close to the predicted symptoms by the machine learning methods. The study was a result of a collaboration between the University of Surrey and the University of California in San Francisco (UCSF).
(Little’s MCAR test, p>0.05). Missing values are due to missing responses from patients.
Credit: PLOS One
"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. They can help clinicians identify high-risk patients, help and support their symptom experience and pre-emptively plan a way to manage those symptoms and improve quality of life,” says Payam Barnaghi, professor of Machine Intelligence at the University of Surrey.
Source: University of Surrey