Accelerating AI development in healthcare

AI building blocks for creating next-gen healthcare solutions.
Health AI Developer Foundations (HAI-DEF) is a collection of open-weight models and companion resources to help developers build AI models for healthcare.
Access pre-trained models to build AI applications, with less data and compute resources.
HAI-DEF model weights are open, so you can run them wherever you'd like and fine-tune them with your data for your tasks.
HAI-DEF models can be deployed on GCP as productionized, scalable services that natively integrate with Vertex AI, Google Cloud Storage, and Google Cloud DICOM Store.

Build with domain-specific models

Each HAI-DEF model is specialized for a specific medical domain. The models are developed using large amounts of diverse data for their respective domains, enabling application development that requires significantly less data and compute than traditional methods.
CXR Foundation accelerates AI development for chest X-ray image analysis. The model is pre-trained on large amounts of chest X-rays paired with radiology reports. It produces language-aligned embeddings that capture dense features relevant for chest X-ray applications.
  • Data-efficient classification
  • Zero-shot classification
  • Semantic image retrieval
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Path Foundation accelerates AI development for histopathology image analysis. The model uses self-supervised learning on large amounts of digital pathology data to produce embeddings that capture dense features relevant for histopathology applications.
  • Data-efficient classification
  • Similar image search
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Derm Foundation accelerates AI development for skin image analysis. The model is pre-trained on large amounts of labeled skin images to produce embeddings that capture dense features relevant for dermatology applications.
  • Data-efficient classification
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Access the HAI-DEF models

Send feedback to: hai-def@google.com

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