MedGemma

MedGemma is Google's open-weight Gemma 3-based model collection for medical text and multimodal medical image comprehension, covering dermatology, pathology, ophthalmology, chest X-ray, and clinical text, released as 4B multimodal and 27B text/multimodal variants. It is trained and evaluated on datasets including MIMIC-CXR, TCGA (cancer genomics data), CAMELYON histopathology, PAD-UFES-20, and SLAKE, and is documented with an unusually formal, separately maintained structured model-card document (developers.google.com/health-ai-developer-foundations/medgemma/model-card) covering intended use, training data, and evaluation, positioning it for clinical-note extraction and clinical-image interpretation workflows that match the PRD's own named example.

Marginal call, stated plainly: MedGemma is a general clinical/health model (dermatology, radiology, pathology, clinical text), not a genomics-native model, even though its training data includes TCGA cancer genomics data as one dataset among many. It implements no GA4GH standard or extension. It is catalogued here as a marginal fit on the genomics-specificity axis, not a clean one, consistent with how this registry has already flagged other general clinical/health models.

Licence note, confirmed directly from Google's own model-card documentation (not derived Hugging Face metadata alone): "The use of MedGemma is governed by the Health AI Developer Foundations terms of use" -- a custom, gated licence (Hugging Face access requires accepting these terms), not a standard open-source SPDX licence, hence license: other with license_url pointing to the terms document itself.

Registry note on model_card_uri: this points to Google's own separately published, structured MedGemma model-card document rather than the gated Hugging Face repository page, since the former is the more authoritative and more fully documented source.