Loading…
Every biological foundation model, evaluated and ranked by the bio.rodeo team
Showing 1–8 of 8 models
Medically tuned SigLIP encoder from Google that maps medical images and text into one embedding space for zero-shot classification and retrieval.
Open medical multimodal models from Google, built on Gemma 3 with a medically tuned SigLIP vision encoder for clinical text and image understanding.
DNA foundation model that predicts thousands of functional genomic tracks, from expression and splicing to chromatin, at single base-pair resolution.
Open therapeutics foundation models from Google, built on Gemma-2, for drug-discovery property prediction and conversational reasoning.
Chest X-ray embedding model built on ELIXR, producing image and image-text embeddings for data-efficient and zero-shot radiograph classification.
Histopathology foundation model that encodes 224x224 H&E patches into compact 384-dimensional embeddings for tumor and biomarker classifiers.
Google's dermatology image embedding model that produces 6144-dimensional embeddings for data-efficient skin-condition classifiers.
Health acoustics foundation model that turns short clips of coughs and breaths into embeddings for building acoustic biomarker models with less data.