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...
保存先:
| 主要な著者: | , , , |
|---|---|
| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
BMC
2026-04-01
|
| シリーズ: | Journal of Cheminformatics |
| 主題: | |
| オンライン･アクセス: | https://doi.org/10.1186/s13321-026-01172-y |
| タグ: |
タグなし, このレコードへの初めてのタグを付けませんか!
|