New artificial intelligence (AI) developed in the UK could help doctors provide more personalised treatment for cancer patients.
Researchers from the Centre for Vision, Speech and Signal Processing (CVSSP) at the University of Surrey created two machine learning models that are both 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.
By predicting the course and severity of these symptoms, doctors can personalise the patient’s treatment regimen more efficiently and provide more aggressive and timely interventions, the researchers explained.
The models were based on existing data of the symptoms experienced by cancer patients undergoing chemotherapy treatment. Different time periods were used in order to test whether the machine learning algorithms could accurately predict if and when symptoms emerged.
Results published in the PLOS One journal show that the actual reported symptoms were very close to those predicted by the machine learning methods.
“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,” said Payam Barnaghi, Professor of Machine Intelligence at the University of Surrey. “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.”
Nikos Papachristou, who worked on designing the machine learning algorithms for this project, added: “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.”
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