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To help RETINA, BALANCED built and crowd-sourced an original video game, Eye in the Sky: Defender.The game uses optical coherence tomography (OCT) retinal images inserted in the game’s environment to design human-computational image segmentation.

 

As players predict the path of the alien force in the game, they unintentionally learn to trace lines used to perform diagnostic measurements of OCT retinal scans and build new datasets.

 

When joined with BALANCED’s HEWMEN® artificial intelligence (AI) platform, these new datasets were used by experts at RETINA and investigators at SMU to supply the details needed to train a machine learning (ML) algorithm to analyze OCT images more accurately and precisely.

“Human and machine collaboration is the next step in machine learning and AI,” noted Corey Clark, deputy director of research and assistant professor of computer science and engineering for SMU Guildhall, an assistant professor of Computer Science at SMU Lyle School of Engineering and CTO at BALANCED.

By leveraging this advanced level of human-in-the-loop (HITL) computational model, as well as human computational gaming (HCG), it’s now possible to use AI to quickly examine millions of individual datasets (retinal images) to discover patterns and pathologies that would have been difficult or impractical given the scope.

This technology would be a game-changer for investigators and drug producers in the data analysis of disease development, drug trials, and treatment efficacy for age-related macular degeneration, among other ailments.

With this technology we are seeing considerable developments to image analysis, decreasing our time and cost, and seeing a remarkable increase in the number of images processed and associated accuracy and precision of image processing.

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