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Every biological foundation model, evaluated and ranked by the bio.rodeo team
Showing 145–168 of 224 filtered models
Pathology vision-language model for whole-slide diagnosis, adding lesion detection and segmentation to visual question answering on gigapixel images.
Spatial gene expression prediction from H&E tumor histology, aligning a pathology foundation model with a single-cell RNA-seq foundation model.
Bilingual Arabic-English medical multimodal model built on Llama 3.1 for radiology, CT, and histology image understanding and question answering.
Whole-slide pathology assistant that states the morphological findings behind each diagnosis, trained on 180k VQA pairs from 9,850 gigapixel slides.
Histopathology patch encoder turning 512x512 tiles into 768-dimensional features, trained with a CoCa objective on 1.26 million captioned images.
Pathology image embeddings supervised by spatial transcriptomics instead of text captions, aligned over 697K image-gene expression pairs.
Slide-level pathology foundation model turning whole-slide images into reusable embeddings for classification, retrieval, and report generation.
Multi-scale latent diffusion model for histopathology that synthesizes tissue patches at any magnification and composes them into 4096-pixel images.
Spatial transcriptomics foundation model aligning histology with gene expression at spot and neighborhood scale for zero-shot tissue domain calling.
Renal pathology segmentation model resolving 14 glomerular tissue, cell, and lesion classes in human and mouse whole-slide images.
Histopathology image synthesis steered by a hand-drawn coarse tissue mask, refined into a fine-grained semantic mask before H&E or IHC rendering.
Virtual staining diffusion model that converts kidney histology between H&E, Masson's trichrome, PAS, and PASM in any direction from one checkpoint.
Prostate histopathology classifiers that split H&E tissue into benign, Gleason 3, 4 and 5 patches and aggregate those calls into an ISUP grade group.
Lung cancer histopathology model that predicts spread through air spaces from whole-slide images using a feature-interactive Siamese graph encoder.
Histopathology foundation model aligned to spatial transcriptomics by a cross-modal ranking loss, embedding H&E patches without gene input.
Slide-level histopathology encoder that contrastively aligns tile embeddings from several patch foundation models through a Mamba-2 aggregator.
Tissue-specific histological aging clocks that read biological age and per-organ age gaps from H&E whole-slide images and from blood gene expression.
Histopathology model predicting extrachromosomal DNA status from routine H&E slides by first inferring the tumor transcriptome from tile features.
Virtual multiplex immunofluorescence staining from H&E histopathology, imputing the expression and spatial localization of 50 protein biomarkers.
Breast cancer recurrence risk read from an H&E slide and six routine clinical variables, using a frozen pan-cancer pathology encoder.
Region-aware bilingual medical multimodal LLM that handles image- and region-level vision-language tasks across eight imaging modalities.
Spatial transcriptomics prediction from H&E slides, inferring spot-level expression and tumor microenvironment composition in breast cancer.
Vision-language assistant that reads a whole gigapixel pathology slide, answering diagnostic questions and writing slide-level descriptions.
Medical imaging embedding model spanning X-ray, CT, MRI, dermoscopy, OCT, fundus, ultrasound, histopathology and mammography in one encoder.