CXR Foundation is a machine learning (ML) model that produces embeddings based on images of chest X-rays. The embeddings can be used to efficiently build AI models for chest X-ray related tasks, requiring less data and less compute than having to fully train a model without the embeddings.
The model has been optimized for chest X-rays, but researchers have reported success using it for other types of X-rays, including X-rays of other body parts and even veterinary X-rays.
As a Health AI Developer Foundations (HAI-DEF) model trained on large scale datasets, CXR Foundation helps businesses and institutions in healthcare and life sciences do more with their chest X-ray data with less data, accelerating their ability to build AI models for chest X-ray image analysis.
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Read our developer documentation to see the full range of next steps available, including learning more about the model through its model card or serving API.
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Explore this repository, which contains notebooks for using the model from Hugging Face and Vertex AI as well as the implementation of the container that you can deploy to Vertex AI.
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Visit the model on Hugging Face or Model Garden.
We are open to bug reports, pull requests (PR), and other contributions. See CONTRIBUTING and community guidelines for details.
While the model is licensed under the Health AI Developer Foundations License, everything in this repository is licensed under the Apache 2.0 license, see LICENSE.