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Editorial · Models
Models with recorded evidence.
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Vendor:Areas overviewSpeakLeash · 263Alibaba · 104Google · 102OpenAI · 86Meta · 68Microsoft · 49Anthropic · 44DeepSeek · 34Mistral · 30mistralai · 19CYFRAGOVPL · 14NVIDIA · 14Zhipu AI · 13internlm · 10xAI · 10ByteDance · 9Baidu · 8ibm-granite · 8PLLuM · 8allenai · 7Amazon · 7MiniMax · 7Mistral AI · 7Remek · 7Shanghai AI Lab · 7utter-project · 7CohereForAI · 6Salesforce · 601-ai · 5Cohere · 5Moonshot AI · 5NousResearch · 5THUML · 5gguf-iq · 4IBM · 4Meituan · 4openchat · 4Stanford · 4THUDM · 4tiiuae · 4UC San Diego · 4VikParuchuri · 4Allen AI · 3BAAI · 3Du et al. · 3ForgeCode · 3Fudan University · 3gguf · 3gguf11bv30 · 3gguf7bv30 · 3IDEA Research · 3Liao et al. · 3Moonshot.AI · 3Nam Tuan Ly / NII · 3OpenDataLab · 3OPI-PG · 3upstage · 3ViCoS Lab Ljubljana · 3Xiaomi · 3Zhao et al. · 3+ 243 smaller vendors (288 models)
§ 01 · Medical models
50 models in Medical · page 1 of 1.
| # | Model | Vendor | Parameters | Architecture | Benchmarks | Results |
|---|---|---|---|---|---|---|
| 001 | TorchXRayVision | Cohen Lab | — | DenseNet-121 / ResNet | 6 | 6 |
| 002 | DenseNet-121 (Chest X-ray) | Research | 8M | DenseNet-121 | 4 | 4 |
| 003 | nnU-Net v2 | German Cancer Research Center (DKFZ) | varies (~31M default) | U-Net (self-configuring) | 4 | 4 |
| 004 | MedNeXt-L | German Cancer Research Center (DKFZ) | 62M | ConvNeXt-based encoder-decoder | 3 | 3 |
| 005 | STU-Net-L | Ziyan Huang et al. | 440M | Scalable U-Net | 3 | 3 |
| 006 | ASDFormer | Research | — | Transformer with Mixture of Experts | 1 | 2 |
| 007 | ASD-SWNet | Research | — | Shared-weight CNN | 1 | 2 |
| 008 | BrainTWT | Academic | — | Temporal Random Walk + Transformer | 1 | 2 |
| 009 | Causal fMRI Model | Academic | — | Causality-inspired Deep Learning | 1 | 2 |
| 010 | ChebGAT-GCN | Academic | — | Chebyshev Spectral GCN + Graph Attention Network | 1 | 2 |
| 011 | CheXNet | Stanford ML Group | 8M | DenseNet-121 | 2 | 2 |
| 012 | CheXzero | Harvard/MIT | — | CLIP-based Vision-Language | 2 | 2 |
| 013 | GCN | Research | — | Graph Convolutional Network | 1 | 2 |
| 014 | MAACNN | Research | — | CNN | 2 | 2 |
| 015 | MVS-GCN | Research | — | Multi-view Site Graph Convolutional Network | 1 | 2 |
| 016 | nnFormer | Zhou et al. | 150M | Interleaved Transformer for volumetric segmentation | 2 | 2 |
| 017 | RAD-DINO | Microsoft | — | Self-supervised ViT | 2 | 2 |
| 018 | Random Forest | scikit-learn | — | Random Forest | 2 | 2 |
| 019 | STU-Net-H | Ziyan Huang et al. | 1.4B | Scalable U-Net | 2 | 2 |
| 020 | SVM with Connectivity Features | Research | — | Support Vector Machine | 1 | 2 |
| 021 | Swin UNETR | NVIDIA (MONAI) | 62M | Swin Transformer encoder + U-Net decoder | 2 | 2 |
| 022 | TransUNet | Chen et al. (JHU) | 105M | ViT encoder + U-Net decoder | 2 | 2 |
| 023 | U-Mamba (Bot) | Wang et al. (University of Toronto) | 59M | Mamba (SSM) + U-Net | 2 | 2 |
| 024 | UNETR | NVIDIA (MONAI) | 93M | Pure ViT encoder + U-Net decoder | 2 | 2 |
| 025 | Abraham Connectomes | Research | — | Connectome Analysis | 1 | 1 |
| 026 | AE-FCN | Research | — | Autoencoder + Fully Connected Network | 1 | 1 |
| 027 | AL-Negat | Research | — | Graph Neural Network | 1 | 1 |
| 028 | BioViL | Microsoft | — | Vision-Language Transformer | 1 | 1 |
| 029 | BrainGNN | Research | — | Graph Neural Network | 1 | 1 |
| 030 | BrainGT | Research | — | Graph Transformer | 1 | 1 |
| 031 | CheXpert AUC Maximizer | Stanford | — | DenseNet-121 Ensemble | 1 | 1 |
| 032 | ConVIRT | NYU | — | Contrastive Vision-Language | 1 | 1 |
| 033 | DeepASD | Research | — | Adversary-regularized GNN | 1 | 1 |
| 034 | Deep Learning (Heinsfeld) | Research | — | Deep Neural Network | 1 | 1 |
| 035 | GLoRIA | Stanford | — | Vision-Language (Local + Global) | 1 | 1 |
| 036 | LightM-UNet | Liao et al. | 4M | Lightweight Mamba + U-Net | 1 | 1 |
| 037 | MADE-for-ASD | Academic | — | Multi-Atlas Deep Ensemble Network | 1 | 1 |
| 038 | MCBERT | Research | — | Multi-modal CNN-BERT | 1 | 1 |
| 039 | MedCLIP | Research | — | CLIP-based Vision-Language | 1 | 1 |
| 040 | MSalNET | Academic | — | Multi-site Adversarial Learning Network | 1 | 1 |
| 041 | Multi-Atlas DNN | Research | — | Deep Neural Network | 1 | 1 |
| 042 | Multi-Task Transformer | Research | — | Transformer | 1 | 1 |
| 043 | PHGCL-DDGFormer | Research | — | Graph Transformer | 1 | 1 |
| 044 | Plymouth DL Model | Research | — | Deep Learning with XAI | 1 | 1 |
| 045 | ResNet-50 (Chest X-ray) | Research | 25M | ResNet-50 | 1 | 1 |
| 046 | RGTNet | Academic | — | Residual Graph Transformer | 1 | 1 |
| 047 | SAM-Med3D | University Medical Center Hamburg-Eppendorf et al. | 387M | SAM adapted for 3D volumes | 1 | 1 |
| 048 | SegMamba | Xing et al. | 53M | Mamba-based 3D segmentation | 1 | 1 |
| 049 | SegVol | BAAI (Beijing Academy of AI) | 90M | SAM-based volumetric segmentation | 1 | 1 |
| 050 | SSAE + Softmax (Explainable ASD) | Academic | — | Stacked Sparse Autoencoder + Softmax | 1 | 1 |