All Competitors
Every biological foundation model, evaluated and ranked by the bio.rodeo team
Showing 1–18 of 18 filtered models
RadiologyNET
57—A family of CNN foundation models pretrained on ~1.9M multimodal radiology images for transfer learning across medical imaging tasks.
Imaging53OpennessMed-R1
126125—A reinforcement-learning-trained medical vision-language model for generalizable reasoning across eight imaging modalities and five clinical question types.
ImagingLanguage model45OpennessFM-CT
5511—A 3D self-supervised foundation model for non-contrast head CT, pretrained on 361,663 scans for generalizable detection of intracranial disease.
Imaging26OpennessMUSK
229246—A vision-language foundation model for precision oncology that pretrains on 50M pathology images and 1B text tokens via unified masked modeling.
PathologyLanguage model12OpennessBrainIAC
12824—A self-supervised vision foundation model for structural brain MRI that produces general-purpose features adaptable to diverse downstream clinical and neuroscience tasks.
Imaging24OpennessUltraSam
13529—A SAM-based foundation model for promptable ultrasound image segmentation, trained on US-43d, the largest assembled public ultrasound segmentation dataset.
Imaging26OpennessMedRegA
452613Hong Kong University of Science and Technology +1 otherOctober 24, 2024histologyimage_classificationinstruction_tuning+8Region-aware bilingual (Chinese-English) medical multimodal LLM that handles image- and region-level vision-language tasks across eight imaging modalities.
PathologyLanguage model65OpennessMaCo
1272—A masked contrastive chest X-ray foundation model that aligns radiograph patches with report text for zero-shot and fine-grained diagnosis.
Imaging74OpennessBiomedGPT
709373—Open-source, lightweight generalist vision-language foundation model for diverse biomedical imaging and text tasks.
Language modelImagingPathology33OpennessMammo-CLIP
94—17Vision-language foundation model pre-trained on screening mammogram-report pairs to improve data efficiency and robustness in breast cancer detection.
ImagingPathology27OpennessLaMIM
1919—West China Hospital of Sichuan University +1 otherApril 17, 2024autoencoderbrain_mrifoundation_model+6Self-supervised vision transformer autoencoder pretrained on ~57,000 multi-contrast brain MRIs via masked image modeling for downstream brain tumor diagnosis.
Imaging15OpennessMed-MoE
15882—A lightweight mixture-of-experts medical vision-language model that routes between domain-specific experts for VQA and image classification while activating only 30-50% of parameters.
ImagingLanguage modelPathology81OpennessCheXagent
226711.3KAn instruction-tuned vision-language foundation model from Stanford for interpreting and summarizing chest X-rays across eight clinical task types.
ImagingLanguage model32OpennessRETFound
636860—University College London +1 otherSeptember 13, 2023disease_detectionfoundation_modelfundus_photography+8A self-supervised foundation model for retinal images, pretrained on 1.6M fundus and OCT scans to detect ocular and systemic disease.
ImagingPathology30OpennessMedBLIP
5785—A vision-language model that bootstraps pre-training from frozen image encoders and LLMs for 3D medical image diagnosis and visual question answering, demonstrated on brain MRI.
ImagingLanguage model35OpennessPMC-CLIP
240——A biomedical vision-language model trained with contrastive learning on 1.6M image-caption pairs (PMC-OA) mined from PubMed Central open-access articles.
PathologyImaging63OpennessCheXzero
229498—Self-supervised vision-language model for zero-shot detection of chest X-ray pathologies, trained on image-report pairs without explicit labels.
ImagingPathology70OpennessMed3D
2.2K653—Pretrained 3D-ResNet backbones trained on aggregated multi-domain medical segmentation data, released as transfer-learning weights for volumetric medical image analysis.
Imaging75Openness