Interestingly, we are working with Dr. Corey Clark and his team at Southern Methodist University, who have the number one gaming department in the country. We are using a gaming platform to try to focus and expedite the machine learning process, so there is not a need for a large dataset going forward. We have some pilot data to support that this could work. There is lots of evidence to support that the interaction between human input and machine learning can be the most productive. From gaming input algorithms, we can apply human intuition to speed up the process and apply it to an OCT image, which rapidly identifies the appropriate feature. For example, in the below image these are drusen transformed into a tank destroying game. If players successfully drive the tank around the hills (that represent the drusen) they get more points.