Case Study – Improving Medical Imaging AI with HEWMEN
Using HEWMEN to Enhance DNN Image Segmentation of Age Related Macular Degeneration OCT images.
BALANCED Solution - HEWMEN Platform Benefits
Improving Model Accuracy
Increased algorithm precision (+78%) and accuracy (+38%)
Reducing Model Size
Decreased computational requirements with increased model accuracy and precision
Leveraging Small Data Sets
Improved algorithm performance vs traditional training models requiring large data sets
Improved algorithm automation allowing experts to pursue more complex problems
Decreased specialists referrals, faster training time, and reduced development and operating costs
To get better treatments to patients faster by enabiling AI
Results from HEWMEN AMD Case Study
Players through human computational gaming (HCG) effectively trained an existing deep learning algorithm to identify retinal disease
Through the HEWMEN platform, BALANCED has a unique approach to training AI algorithms. Our ability to do so using smaller data sets with greater accuracy and precision at higher margins than conventional techniques provides an exclusive advantage to our customers/partners.
Our Published Papers
- C. Clark and M. Ouellette, “Using Human Computation Game-Based Input to Enhance DNN Image Segmentation of Age-Related Macular Degeneration OCT Images with Small Datasets,” IEEE Transactions on Pattern Analysis and Machine Intelligence, 2020 (Under Review)
- C. Clark, M. Ouellette, and K. Csaky, “Training Players to Analyze Age-Related Macular Degeneration Optical Coherence Tomography Scans using a Human Computation Game,” in 2019 IEEE 7th International Conference on Serious Games and Applications for Health (SeGAH), Kyoto, Japan, Aug. 2019, pp. 1–7, doi: 10.1109/SeGAH.2019.8882430.
- C. Clark, I. Greenberg, and M. Ouellette, “A model for integrating human computing into commercial video games,” in 2018 IEEE 6th International Conference on Serious Games and Applications for Health (SeGAH), Vienna, May 2018, pp. 1–8, doi: 10.1109/SeGAH.2018.8401316.
- C. Clark and M. Ouellette, “Video games as a distributed computing resource,” in Proceedings of the International Conference on the Foundations of Digital Games - FDG ’17, Hyannis, Massachusetts, 2017, pp. 1–7, doi: 10.1145/3102071.3102099.