{"count":1,"items":[{"article":null,"cancer_slugs":["pan-cancer"],"category":"clinical-LLM","confidence":"medium","developer":"Google (Health AI Developer Foundations)","hf":{"downloads":1105085,"fetched_at":"2026-09-09T21:33:09Z","gated":"auto","last_modified":"2025-10-28","library":"transformers","license":"other","likes":1048,"pipeline_tag":"image-text-to-text"},"kind":"foundation","license":"Health AI Developer Foundations terms of use","links":{"demo":null,"docs":"https://developers.google.com/health-ai-developer-foundations/medgemma","doi":null,"github":null,"huggingface":"https://huggingface.co/google/medgemma-4b-it","paper":"https://arxiv.org/abs/2507.05201","pmid":null},"modalities":["multimodal","radiology-xray","histopathology","dermoscopy","clinical-text"],"name":"MedGemma","openness":"gated-weights","regulatory_status":"research-only","release_date":"2025-05-20","settings":["basic-research","education"],"slug":"medgemma","summary":"Open-weight medical vision-language models built on Gemma 3: the 4B variant reads chest X-rays, dermatology, ophthalmology and histopathology images alongside text; the 27B variant targets medical text reasoning. Meant as a starting point for developers to fine-tune, not as a finished clinical product.","tasks":["question-answering","report-generation","classification","information-extraction"],"url":"/ai-oncology/models/medgemma","verified_at":"2026-09-05T22:26:00.309905","version":"4B multimodal / 27B text"}],"standard":"https://cancer3.ai/docs/ai-model-card","vocab":{"confidence":["high","medium","low"],"dataset_access":["open","registration","dua","controlled","commercial"],"dataset_kinds":["dataset","registry","benchmark","biobank","corpus"],"formats":["SVS","TIFF","NDPI","DICOM","NIfTI","PNG","JPEG","CSV","TSV","JSON","Parquet","FASTQ","BAM","VCF","MAF","h5ad","PDB","mmCIF","text","other"],"kinds":["foundation","task-model","tool","framework","product"],"link_roles":["pretraining","training","finetuning","evaluation","benchmark"],"modalities":["histopathology","radiology-ct","radiology-mri","radiology-xray","mammography","pet","ultrasound","dermoscopy","endoscopy","genomics","transcriptomics","single-cell","proteomics","protein-sequence","molecules","clinical-text","literature","ehr","multimodal","immunopeptidomics"],"need_status":["open","in-progress","solved"],"openness":["open-weights","gated-weights","api-only","closed"],"regulatory":["research-only","fda-cleared","fda-de-novo","fda-pma","ce-marked","ce-ivdr","not-applicable"],"settings":["basic-research","screening","diagnosis","prognosis","treatment-planning","treatment-response","drug-discovery","clinical-trials","education","vaccine-design","immunotherapy"],"tasks":["feature-extraction","classification","segmentation","detection","screening","risk-prediction","prognosis","treatment-response","survival-analysis","image-text-retrieval","report-generation","question-answering","information-extraction","clinical-trial-matching","protein-structure","variant-effect","gene-expression","single-cell","drug-discovery","drug-repurposing","peptide-mhc-binding","antigen-presentation","neoantigen-prioritisation"]}}