Jan. 2 (UPI) -- A new artificial intelligence method could help doctors identify early cancer symptoms, a new study says.
Researchers at the University of Surrey in England and the University of California in San Francisco collaborated to develop two machine learning models that could predict the severity of depression, anxiety and sleep disturbance, three early symptoms in cancer patients.
Their work was published Monday in the journal 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," Payam Barnaghi, a professor of machine intelligence at the University of Surrey, said in a news release. "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."
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The researchers used machine learning algorithms to examine cancer patient symptoms data from tomography x-ray treatment over various time periods. They found that the AI predictions matched up closely with the original symptom reports.
In 2017, Google unveiled a similar AI tool called Lymph Node Assistant, or LYNA, which delivered gigapixel-sized pathology slides breast cancer patient's lymph nodes to detect metastatic cancer.
Last year the National Institutes of Health estimated that more than 1.7 million people were diagnosed with cancer in the United States,
"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," Nikos Papachristou, a researcher at the University of Surrey.
