.png){kind=icon}
.png){kind=icon}
Return
Predicting synthetic viability
.png){kind=icon}
PRE
AI
DOI：10.1038/s44160-023-00297-4.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Retrosynthesis has served as a playground for computer-aided design for many decades. Computer-aided methods are usually predicated on human-expert rules or learning algorithms that extract the rules from literature data. Now, an approach that bridges the gap between these computer-driven methods and the traditional, intuition-driven, 'chalk board' retrosynthetic methods is reported.