RYVER.AI
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About
RYVER enables medical AI teams to generate high-quality radiology images with annotations, reducing time and cost in data acquisition. It improves accuracy and robustness by using generative models to augment proprietary data and oversample underrepresented subgroups. RYVER models add diversity by being pre-trained on rich medical data from multiple partners. It saves 80-90% in cost per image by substituting data acquisition and annotation efforts, and enables faster development by generating additional data in minutes instead of months.
Platform
Task
Features
• python library for using synthetic data
• graphical interface for discovering synthetic data resources
• embeddings and evaluation of downstream performance improvement of diagnostic models
• frameworks and tools to assess the utility of synthetic data
• synthetic data generation with a few lines of code
• python libraries for integrating generative models into data pipelines
• fine-tuning with proprietary data without compromising data security or privacy
• generative models pre-trained on high-quality medical imaging data sets
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