Awesome-Biomedical-World-Models

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Awesome-Biomedical-World-Models

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Collect papers on world models for biomedicine.

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# Awesome-Biomedical-World-Models

[![Awesome](https://cdn.rawgit.com/sindresorhus/awesome/d7305f38d29fed78fa85652e3a63e154dd8e8829/media/badge.svg)](https://github.com/sindresorhus/awesome) [![arXiv](https://img.shields.io/badge/Arxiv-2606.05925-b31b1b.svg?logo=arXiv)](https://arxiv.org/abs/2606.05925v1) [![GitHub stars](https://img.shields.io/github/stars/Yuejingkun/Awesome-Biomedical-World-Models?style=social)](https://github.com/Yuejingkun/Awesome-Biomedical-World-Models)

A curated collection of papers, datasets, benchmarks, and resources related to Biomedical World Models, as a supplement to our [Paper](https://arxiv.org/abs/2606.05925v1).

*Photo Credit: GPT Image 2*.
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## News & Updates

**[2026-06]** Repository Launch -- Awesome Biomedical World Models is now live!

---

## Overview

- 🦠 [World Models for Molecular and Cellular Dynamics](#world-models-for-molecular-and-cellular-dynamics)
- 🫀 [World Models for Virtual Organoids](#world-models-for-virtual-organoids)
- 👤 [World Models for Virtual Patients and Clinical Decision-Making](#world-models-for-virtual-patients-and-clinical-decision-making)
- 🪡 [World Models for Surgical Simulation and Embodied Autonomy](#world-models-for-surgical-simulation-and-embodied-autonomy)
- 📊 [Data](#data)
- 📣 [Contributing](#contributing)
- 🙏 [Acknowledgements](#acknowledgements)
- 🌟 [Citation](#citation)

---

## World Models for Molecular and Cellular Dynamics
- **Lingshu-Cell**, "Lingshu-Cell: A generative cellular world model for transcriptome modeling toward virtual cells". [[Paper](https://arxiv.org/abs/2603.25240)] [[Website](https://alibaba-damo-academy.github.io/lingshu-cell-homepage/)]
- **AlphaCell**, "Towards building a World Model to simulate perturbation-induced cellular dynamics by AlphaCell". [[Paper](https://www.biorxiv.org/content/10.64898/2026.03.02.709176v1)]
- **Chreode**, "Chreode: A Cell World Model for One-Step Temporal Dynamics and Perturbation Prediction". [[Paper](https://arxiv.org/abs/2605.28111v1)]
- **VCWorld**, "VCWorld: A Biological World Model for Virtual Cell Simulation". [[Paper](https://arxiv.org/abs/2512.00306)] [[Code](https://github.com/GENTEL-lab/VCWorld)]
- **MOLWORLD**, "MOLWORLD: Molecule World Models for Actionable Molecular Optimization". [[Paper](https://arxiv.org/abs/2605.08954)]
- **ODesign**, "ODesign: A World Model for Biomolecular Interaction Design". [[Paper](https://arxiv.org/abs/2510.22304)] [[Code](https://github.com/OTeam-AI4S/ODesign)] [[Website](https://odesign1.github.io/)]
- **CellOS**, "CellOS: Learning a World Model of Cellular State through Joint Embedding Prediction". [[Paper](https://www.biorxiv.org/content/10.64898/2026.06.18.733163v1)]
- **MicroVerse**, "MicroVerse: A Preliminary Exploration Toward a Micro-World Simulation". [[Paper](https://arxiv.org/abs/2603.00585)] [[Code](https://github.com/FreedomIntelligence/MicroVerse)]

---

## World Models for Virtual Organoids
- **V3Cell**, "V3Cell: A Vision-Guided Virtual 3D Cell Framework for Phenotypic Modeling and Perturbation Prediction". [[Paper](https://www.biorxiv.org/content/10.64898/2026.06.23.734130v1)] [[Code](https://github.com/Laineyoulu/V3Cell)]

---

## World Models for Virtual Patients and Clinical Decision-Making
- **ChexWorld**, "CheXWorld: Exploring Image World Modeling for Radiograph Representation Learning". [[Paper](https://arxiv.org/abs/2504.13820)] [[Code](https://github.com/LeapLabTHU/CheXWorld)]
- **EchoWorld**, "EchoWorld: Learning Motion-Aware World Models for Echocardiography Probe Guidance". [[Paper](https://arxiv.org/abs/2504.13065)] [[Code](https://github.com/LeapLabTHU/EchoWorld)]
- **X-WIN**, "X-WIN: Building Chest Radiograph World Model via Predictive Sensing". [[Paper](https://arxiv.org/abs/2511.14918)] 
- **Xray2Xray**, "Xray2Xray: World Model from Chest X-rays with Volumetric Context". [[Paper](https://arxiv.org/abs/2506.19055)]
- **MeWM**, "Medical World Model: Generative Simulation of Tumor Evolution for Treatment Planning". [[Paper](https://arxiv.org/abs/2506.02327)] [[Code](https://github.com/scott-yjyang/MeWM)] [[Website](https://yijun-yang.github.io/MeWM/)]
- **CLARITY**, "CLARITY: Medical World Model for Guiding Treatment Decisions by Modeling Context-Aware Disease Trajectories in Latent Space". [[Paper](https://arxiv.org/abs/2512.08029)] [[Code](https://github.com/DingTianxingjian/CLARITY)] [[Website](https://dingtianxingjian.github.io/clarity-project-page/)]
- **EyeWorld**, "EyeWorld: A Generative World Model of Ocular State and Dynamics". [[Paper](https://arxiv.org/abs/2603.14039)]
- **Brain-WM**, "Brain-WM: Brain Glioblastoma World Model". [[Paper](https://arxiv.org/abs/2603.07562)] [[Code](https://github.com/thibault-wch/Brain-GBM-world-model)]
- **EHRWorld**, "EHRWorld: A Patient-Centric Medical World Model for Long-Horizon Clinical Trajectories". [[Paper](https://arxiv.org/abs/2602.03569)] 
- **MRI CEK-World**, "MRI Contrast Enhancement Kinetics World Model". [[Paper](https://arxiv.org/abs/2602.19285)] [[Code](https://github.com/DD0922/MRI-Contrast-Enhancement-Kinetics-World-Model)]
- **Cardiac World Model**, "Structure-aware World Model for Probe Guidance via Large-scale Self-supervised Pre-train". [[Paper](https://arxiv.org/abs/2406.19756v2)]
- **Cardiac Copilot**, "Cardiac Copilot: Automatic Probe Guidance for Echocardiography with World Model". [[Paper](https://arxiv.org/abs/2406.13165v2)]
- **SepsisAgent**, "Agentifying Patient Dynamics within LLMs through Interacting with Clinical World Model". [[Paper](https://arxiv.org/abs/2605.14723)] [[code](https://github.com/FreedomIntelligence/SepsisAgent)]
- **DiagGym**, "Evolving Interactive Diagnostic Agents in a Virtual Clinical Environment". [[Paper](https://arxiv.org/abs/2510.24654)] [[Code](https://github.com/MAGIC-AI4Med/DiagGym)]
- **TwinRL-Onco**, "TwinRL-Onco: A World Model-Empowered Digital Twin Framework with Hierarchical Reinforcement Learning for Venetoclax Resistance Trajectory Prediction and Adaptive Therapy Optimization in Chronic Lymphocytic Leukemia". [[Paper](https://ieeexplore.ieee.org/document/11535005)]
- **MedGenesis**, "MedGenesis: Toward a World Model for
Autonomous Clinical and Translational Research". [[Paper](https://www.medrxiv.org/content/10.64898/2026.06.14.26355612v1)]
- **HounsWorld**, "HounsWorld: A Multimodal World Model for Hidden Patient-State Readout, Reconstruction, and Simulation". [[Paper](https://arxiv.org/abs/2608.12904)] [[Code](https://github.com/byhwhite/HounsWorld)]

---

## World Models for Surgical Simulation and Embodied Autonomy
- **GAS**, "World Models for General Surgical Grasping". [[Paper](https://arxiv.org/abs/2405.17940)] [[Code](https://github.com/linhongbin/gas)] [[Website](http://hongbinlin.com/gas/)]
- **SurgWM**, "Surgical Vision World Model". [[Paper](https://arxiv.org/abs/2503.02904)] [[Code](https://github.com/bhattarailab/Surgical-Vision-World-Model)]
- **SurgVeo**, "How Far Are Surgeons from Surgical World Models? A Pilot Study on Zero-shot Surgical Video Generation with Expert Assessment". [[Paper](https://arxiv.org/abs/2511.01775)]
- **MedOS**, "MedOS: AI-XR-Cobot World Model for Clinical Perception and Action". [[Paper](https://medos-ai.github.io/assets/logos/MedOS-paper.pdf)] [[Website](https://medos-ai.github.io/)]
- **Cosmos-H-Surgical**, "Cosmos-H-Surgical: Learning Surgical Robot Policies from Videos via World Modeling". [[Paper](https://arxiv.org/abs/2512.23162)] [[Code](https://github.com/NVIDIA-Medtech/Cosmos-H-Surgical)]
- **Cosmos-Surg-dVRK**, "Cosmos-Surg-dVRK: World Foundation Model-based Automated Online Evaluation of Surgical Robot Policy Learning". [[Paper](https://arxiv.org/abs/2510.16240)]
- **Suturing World Model**, "Towards Suturing World Models: Learning Predictive Models for Robotic Surgical Tasks". [[Paper](https://arxiv.org/abs/2503.12531)] [[Website](https://mkturkcan.github.io/suturingmodels/)]
- **SAW**, "SAW: Toward a Surgical Action World Model via
Controllable and Scalable Video Generation". [[Paper](https://arxiv.org/abs/2603.13024)]
- **SWoMo**, "SWoMo: Neuro-Symbolic World Model for Cataract Surgery Simulation". [[Paper](https://arxiv.org/abs/2605.16530)] [[Code](https://github.com/MECLabTUDA/SWoMo)] [[Website](https://ssharvienkumar.github.io/SWoMo/)]
- **SurgVista**, "SurgVista: Long-Horizon Surgical World Modeling
with Plausible Instrument-Tissue Dynamics". [[Paper](https://arxiv.org/abs/2606.19889)]
- **Surg-UniWorld**, "Surg-UniWorld: A Unified Surgical World Model with Multimodal Control Experts". [[Paper](https://arxiv.org/abs/2608.06770)]
- **CrossScope**, "CrossScope: A Role-Asymmetric World Model for Joint Dual-Scope Surgical Video Prediction". [[Paper](https://arxiv.org/abs/2608.03211)]
- **S2-HWM**,  "S2-HWM: Sparse Event-Structured Hierarchical World Model for Long-Horizon Surgical Robot Manipulation". [[Paper](https://arxiv.org/abs/2608.13103)]

---

## Other

- "Did the Grid Erase the Event? EndoClock for Auditing Medical World-Model Pipelines". [[Paper](https://arxiv.org/pdf/2608.09266)]

---

## Challenge

- International Workshop on Medical World Model (MWM) in MICCAI 2026. [[Website](https://mwm2026.github.io/)]

---

## Data

- **Open-H-Embodiment**, "Open-H-Embodiment: A Large-Scale Dataset
for Enabling Foundation Models in Medical Robotics". [[Paper](https://arxiv.org/abs/2604.21017)] [[Website](https://open-h.github.io/open-h-embodiment/)]

---

## Contributing

If you know of any relevant papers missing from this list, feel free to open an issue or submit a pull request. Any contribution that helps make this repository more comprehensive is welcome.

---

## Acknowledgements

This project is largely inspired by the following awesome lists:
- [Awesome World Models for Autonomous Driving](https://github.com/LMD0311/Awesome-World-Model)
- [Awesome World Models for Robotics](https://github.com/leofan90/awesome-world-models)
- [Awesome World Models](https://github.com/knightnemo/Awesome-World-Models)

We appreciate their open-source efforts in curating world model research across different domains.

## Citation

If you find this repository useful in your research, please consider giving a star and citation.

```Bibtex
@article{wang2026towards,
  title={Towards World Models in Biomedical Research},
  author={Wang, Guangyu and Yue, Jingkun and Zhang, Siqi and Liu, Yu and Wang, Xiaoyu and Meng, Mingyuan and Ji, Changwei and Han, Zongbo and Wang, Yulin and Yue, Yang and others},
  journal={arXiv preprint arXiv:2606.05925},
  year={2026}
}
```

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