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Deep learning-based automatic action extraction from structured chemical synthesis procedures
This article proposes a methodology that uses machine learning algorithms to extract actions from structured chemical synthesis procedures, thereby bridging the gap between chemistry and natural language processing. The proposed pipeline combines ML algorithms and scripts to extract relevant data fr...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
PeerJ Inc.
2023
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10495970/ https://www.ncbi.nlm.nih.gov/pubmed/37705639 http://dx.doi.org/10.7717/peerj-cs.1511 |