Overview
GoCheck Kids Leverages Machine Learning to Enhance Pediatric PhotoscreeningProvectus |
Analytics & Modeling - Computer Vision Software Analytics & Modeling - Machine Learning | |
Cement Education | |
Maintenance Product Research & Development | |
Clinical Image Analysis Construction Management | |
Data Science Services Training | |
Operational Impact
The new machine learning infrastructure on AWS supported regular model retraining, evaluation, tuning, and improvements to machine learning models as new labeled data and feedback arrived. More efficient data preparation and faster experimentation enabled GCK to increase the recall of machine learning models by 3X while preserving its precision. This brought in both short and long-term benefits, including improved usability of the app and increased customer satisfaction, by decreasing the final results of 'child not looking' by asking the user to retake the image. The robust and resilient infrastructure for machine learning bolsters GoCheck's quick, sustainable growth in the vision screening market. The GCK application is now equipped with advanced machine learning algorithms that further enable accurate and convenient photoscreening for a wide range of conditions, including amblyopia. Better access to affordable eye screening with GCK means that millions of children will be diagnosed in time, and will not suffer from vision impairments and blindness as adults. | |
Quantitative Benefit
Increased the recall of machine learning models by 3X while preserving precision | |
Conducted over 100 large-scale experiments in three weeks by three machine learning engineers | |
95% of machine learning engineers' time is now exclusively dedicated to experimentation | |