AI-assisted interpretation of Markush structures in pharmaceutical patents: a review of emerging tools, datasets, and challenges

Abstract Automated interpretation of Markush structures widely used in pharmaceutical patents to claim large families of related compounds remains challenging due to non-machine-readable structure images, variable R-groups, dependency rules, scaffold diversity, and heterogeneous claim language. Chal...

全面介紹

書目詳細資料

Principais autores:	Jennifer M. Umbles Hayes, Emmanuel O. Olawode, Anietie Andy, Edmund Essah Ameyaw
格式:	Artigo
語言:	Inglês
出版:	BMC 2026-04-01
叢編:	Journal of Cheminformatics
主題:	Markush claims Cheminformatics Patent analytics Information extraction Large language models (LLMs) Multimodal learning
在線閱讀:	https://doi.org/10.1186/s13321-026-01172-y
標簽:	添加標簽 沒有標簽, 成為第一個標記此記錄!