Cancer patients who undergo chemotherapy could soon benefit from a new AI that is able to identify and predict the development of different combinations of symptoms, according to research from the University of Surrey and the University of California.
Published by Nature Scientific Reports, researchers detail how they used Network Analysis (NA) to examine the structure and relationships between 38 common symptoms reported by over 1300 cancer patients receiving chemotherapy.
Payam Barnaghi, professor of machine intelligence at the Centre for Vision, Speech and Signal Processing (CVSSP) at the University of Surrey, said: “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. The detailed and intricate analysis this method provides could become crucial in planning the treatment."
Some of the most common symptoms reported by patients were nausea, difficulty concentrating, fatigue, drowsiness, dry mouth, hot flushes, numbness, and nervousness.
The team then grouped these symptoms into three key networks – occurrence, severity and distress. The NA allowed the team to identify nausea as central – impacting symptoms across all three different key networks.
Professor Adrian Hilton, director of CVSSP, said: “This is another heartening development from Professor Barnaghi and his group. This world-first study of how NA methods can help identify and analyse the symptoms of cancer patients supports the real benefits machine learning brings to society and the future of the healthcare industry.”
Read the full report here.
