Scientists from the University of Surrey and the University of California have used artificial intelligence network to identify and analyze the symptoms of cancer patients.
A new study, published by Nature Scientific Reports, describes that researchers have used network analysis to examine the structure and relationship between 38 common symptoms reported by over 1300 cancer patients receiving chemotherapy.
This is the first use of network analysis as a method of examining the relationship between common symptoms suffered by a large group of cancer patients who are undergoing chemotherapy. The NA allowed the team to identify nausea as central, impacting symptoms across all three kinds of key networks.
Along with technologies like remote health monitoring system, the development and use of AI is getting popular in the medical field, especially in diagnostic and treatment management.
The ability of AI to grasp and learn from the data presents the opportunity for improved accuracy based on feedback responses. The feedback includes many backed database sources, input from practitioners, doctors, and research institutions.
The AI systems in healthcare are always working in real time, which implies that the data is always updating, thus improving accuracy and relevance.