$GTCH GBT's research is focused on the investigation of Kirlian images with the use of machine learning technology to possibly detect early disease symptoms. GBT’s research within this domain included imaging analytics and graphical experiments in attempt to achieve findings to correlate auras with possible medical symptoms. Using advanced imaging algorithms, Kirlian images were analyzed for patterns, associated colors and shapes. Kirlian imaging produces features such as graphical protuberances, halos, and discharge patterns, which were analyzed and categorized as a possible criterion. GBT believes it has reached viable graphical results and will now move into checking possible health related correlations and implementations. GBT plans to further experiment to analyze energy fields generated by living organs and based on future conclusions will evaluate the implementation of such techniques within its qTerm human vitals product to provide further vital health information.