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KDD'26 Oral | FetalMind: Epistemic-aware Vision–Language Foundation Model for Fetal Ultrasound Interpretation

Xiao He*,1, Huangxuan Zhao*,†,1, Guojia Wan1, Jiancheng Pan2, Yanxing Liu3

Xin Zou4, Yong Luo5, Yongchao Xu5, Juhua Liu1, Wei Zhou6, Dacheng Tao7, Bo Du†,1

1 Wuhan University;  2 Tsinghua University;  3 University of the Chinese Academy of Sciences;
4 HKUST (Guangzhou);  5 Renmin Hospital of Wuhan University;  6 Wuhan Supercomputing Center;  7 Nanyang Technological University

* *Equal contribution*     † *Corresponding author*

News | Open Source | Abstract | Statement

## News - [2026/07] Our FetalMind won the Best Paper Award 🏆 (AI4Science Track). - [2026/05/17] Our FetalMind is accepted by KDD 2026 (Oral, CCF-A). Congrats to our team! - [2025/12/20] We are enhancing the security of the model, which will be uploaded to Hugging Face at this time. - [2025/12/20] We are enhancing the security of the model, which will be uploaded to Hugging Face at this time. - [2025/10/16] The paper and project report have been released. - [2025/10/15] We are actively working to obtain the necessary approvals for dataset release and plan to make a partially de-identified version publicly available after the paper is accepted. ## Open Source The implementation of **FetalMind**, our deconfounded multimodal AI system for fetal ultrasound interpretation, is available on GitHub.

DeepFetal Open Source

## Abstract A fetal vision–language foundation model, **FetalMind**, pretrained on multi-center fetal ultrasound data, integrating structured clinical knowledge and reinforcement learning for report generation and diagnostic reasoning across diverse gestational stages.

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## Statement ### Acknowledgement Sincerely thank [Jiancheng Pan](https://jianchengpan.space/) and [Yanxing Liu](https://yanxingliu.github.io/) for their valuable contributions and support to this project. ### Citation If you are interested in the following work or want to use our dataset, please cite the following paper. ``` @misc{he2025fetalmind, title={Epistemic-aware Vision-Language Foundation Model for Fetal Ultrasound Interpretation}, author={Xiao He, Huangxuan Zhao, Guojia Wan, Jiancheng Pan, Yanxing Liu, Xin Zou, Yong Luo, Yongchao Xu, Juhua Liu, Wei Zhou, Dacheng Tao, Bo Du}, year={2025}, eprint={2505.12953}, archivePrefix={arXiv}, primaryClass={cs.CV}, url={https://arxiv.org/abs/2510.12953}, } ```