A new artificial intelligence technique is able to identify and predict the development of different combinations of symptoms in cancer patients undergoing chemotherapy, according to recent research.
Researchers from the University of Surrey in Guildford, U.K., and UC San Francisco used Network Analysis to analyze the structure and relationships between 38 common symptoms reported by 1,300 cancer patients to develop their AI technique.
The most common symptoms cancer patients reported while undergoing chemotherapy were nausea, difficulty concentrating, fatigue, drowsiness, dry mouth, hot flushes, numbness and nervousness. Researchers grouped these symptoms into three key networks: occurrence, severity and distress.
Network analysis allowed the researchers to identify nausea as a central symptom, meaning it impacted symptoms across all three networks.
The researchers published their findings in Scientific Reports Feb. 19.
"This is the first use of Network Analysis as a method of examining the relationships between common symptoms suffered by a large group of cancer patients undergoing chemotherapy," Payam Barnaghi, a professor at the University of Surrey and co-author on the study, said in a news release. "The detailed and intricate analysis this method provides could become crucial in planning the treatment of future patients — helping to better manage their symptoms across their healthcare journey."