Medical diagnosis prediction using genetic programming

Medical decision making is one of the most demanding tasks in modern medicine. Based on a huge amount of solved cases and rapidly growing number of new findings, medical decision making is supposed to become more and more reliable and effective. However, physicians and medical experts are facing a new arising problem - information overload which they are not able to overcome. A solution might be found in decision support systems with intelligent information processing abilities that help to process a huge amount of data and suggest a possible decision for each new case. Regarding the simplicity of decision trees and effectiveness of evolutionary programming techniques we developed a decision support system based on automatic programming and used it to solve the mitral valve prolapse classification problem.