Integrating MedGemma into clinical workflows just got easier!

Our team, Google Heath AI Developer Foundations, introduced MedGemma earlier this year in May and later followed up in July with a 27-billion-parameter multimodal variant plus MedGemma’s vision encoder: MedSigLIP. We’ve been humbled by the wide variety of model adaptations, research papers, and applications MedGemma has created across academia and industry!

Our aim is to meet you where you are in your research, development, and clinical integration journey. In the earlier releases, we prioritized simplicity, where image prompts were constructed from pixels decoded from non-medical image formats such as JPEG and PNG, and medical record snippets were fed into the model in JSON format or as plain text.

However, we acknowledge the complexities of integrating MedGemma into clinical workflows in an interoperable way. That’s why standard protocols like Digital Imaging and Communications in Medicine (DICOM) and Fast Healthcare Interoperability Resources (FHIR) are crucial for integration into clinical ...