Update README.md

README.md

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 Data processing and annotation is one of the important steps in training the model. We sincerely welcome Traditional Chinese Medicine practitioners with strong TCM thinking and innovative spirit to join us. We will also declare corresponding data contributions. We look forward to the day when we can achieve a reliable General Artificial Intelligence for Traditional Chinese Medicine, allowing the ancient Chinese medicine to blend with modern technology and shine anew. This is also the ultimate mission of this project. If interested, please send an email to [email protected].
 
 ## Team Introduction
-This project is jointly guided by Professor Zhang Wenqiang from Fudan University, Postdoctoral Fellow Wang Yan from Fudan University, and Professor Wang Haofen from Tongji University. The team effort includes Kang Yanlan, Chang Yang, and Fu Jiyuan from Fudan University's [ROI Lab](https://www.fudanroilab.com/), as well as Xing Haozhe in completing this project. Special thanks to the medical team from the Longhua Hospital affiliated with Shanghai University of Traditional Chinese Medicine, including Wu Sunsi, Ma Qingshan, Fang Yide, Chen Yue, Jiao Yuqi, Liu Xiyu, and Zhao Xue for their valuable data support and manual assessments.
+Led by the non-profit organization FulPhil-医哲未来 (Future Medicine Philosophy), the CMLM (Chinese Medicine Language Models) initiative on HuggingFace is dedicated to advancing healthcare AI by integrating traditional Chinese medicine with state-of-the-art machine learning. Our mission includes curating valuable medical datasets, developing AI models for medical assistance, and ensuring ethical AI use in healthcare, fostering collaboration between global experts in Chinese and Western medicine and AI.
 
 ## Citation
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