Feng Pan

Mar 13, 2024 | healio.com | Justin Cooper |Shenaz Bagha |Feng Pan

You've successfully added to your alerts. You will receive an email when new content is published. Click Here to Manage Email Alerts We were unable to process your request. Please try again later. If you continue to have this issue please contact [email protected]. Key takeaways: Diets rich in fats, oils and sweets were associated with worse pain, but not to changes in knee structure. Diet can be part of a comprehensive approach to manage osteoarthritis pain, researchers said.

Jan 26, 2024 | science.org | Rui Peng |Yuriko N. Koyanagi |Clémentine Eva Philibert |Seunghyun Moon |Xizhi Fu |Yichi Zhang | +15 more

Research Article PHYSICS Lei Han https://orcid.org/0000-0001-6152-0307, Xizhi Fu, [...] , Rui Peng, Xingkai Cheng, [...] , Jiankun Dai, Liangyang Liu https://orcid.org/0000-0003-0943-5468, Yidian Li, Yichi Zhang, Wenxuan Zhu, [...] , Hua Bai https://orcid.org/0000-0002-4853-4349, Yongjian Zhou https://orcid.org/0000-0003-4275-8234, Shixuan Liang, Chong Chen, Qian Wang, Xianzhe Chen https://orcid.org/0000-0002-8079-8838, Luyi Yang https://orcid.org/0000-0001-6260-1395, Yang Zhang...

Dec 12, 2023 | biorxiv.org | Yuan Zhang |Feng Pan |Xin Sui |Kaixian Yu

AbstractTo cope with the rapid growth of scientific publications and data in biomedical research, knowledge graphs (KGs) have emerged as a powerful data structure for integrating large volumes of heterogeneous data to facilitate accurate and efficient information retrieval and automated knowledge discovery (AKD). However, transforming unstructured content from scientific literature into KGs has remained a significant challenge, with previous methods unable to achieve human-level accuracy.

Nov 1, 2023 | onlinelibrary.wiley.com | Feng Pan |Zhenyu Li |Shiming Yan |Liyuan Long

Conflict of Interest The authors declare no conflict of interest. Supporting Information Filename Description smll202304846-sup-0001-SuppMat.pdf2.2 MB Supporting information References 1, , , , , , , , , , , , Nat. Commun. 2018, 9, 3366. 2, , , , , , , , , , , , Adv. Mater. 2022, 34, 2110610. 3, , , , , , , , Nat. Energy 2021, 6, 388. 4, , , , , , , , Chem. Eng. J. 2022, 435, 135074. 5, , , , , , , , , Angew. Chem., Int. Ed. 2022, 62, 202210804. 6, , , , , , , , , Nat.

Oct 17, 2023 | biorxiv.org | Yuan Zhang |Feng Pan |Xin Sui |Kaixian Yu

AbstractTo cope with the rapid growth of scientific publications and data in biomedical research, knowledge graphs (KGs) have emerged as a powerful data structure for integrating large volumes of heterogeneous data to facilitate accurate and efficient information retrieval and automated knowledge discovery (AKD). However, transforming unstructured content from scientific literature into KGs has remained a significant challenge, with previous methods unable to achieve human-level accuracy.