MetaRF: attention-based random forest for reaction yield prediction with a few trails

Artificial intelligence has deeply revolutionized the field of medicinal chemistry with many impressive applications, but the success of these applications requires a massive amount of training samples with high-quality annotations, which seriously limits the wide usage of data-driven methods. In th...

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Detalles Bibliográficos
Autores principales: Chen, Kexin, Chen, Guangyong, Li, Junyou, Huang, Yuansheng, Wang, Ercheng, Hou, Tingjun, Heng, Pheng-Ann
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2023
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10084704/
https://www.ncbi.nlm.nih.gov/pubmed/37038222
http://dx.doi.org/10.1186/s13321-023-00715-x

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10084704/
https://www.ncbi.nlm.nih.gov/pubmed/37038222
http://dx.doi.org/10.1186/s13321-023-00715-x

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