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- W4367149210 abstract "Researchers are launching an open-source database of chemical synthesis procedures that they think will benefit artificial intelligence algorithms for reaction prediction, synthesis planning, and other tasks ( J. Am. Chem. Soc. 2021, DOI: 10.1021/jacs.1c09820 ). Machine-learning algorithms typically become more accurate when they are trained on large amounts of data. Machine-learning tools that can identify faces and translate text have become ubiquitous and are accurate because their developers have been able to take advantage of open databases of text and images, according to Steven Kearnes of Relay Therapeutics, a member of the governing committee of the new Open Reaction Database (ORD). Chemists and computer scientists have already demonstrated machine-learning tools that can successfully plot synthetic routes, predict reaction products, and estimate the properties of new compounds. But Kearnes and his colleagues think access to more data is needed to accelerate progress in this area of research. The ORD is designed" @default.
- W4367149210 created "2023-04-28" @default.
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- W4367149210 date "2021-12-06" @default.
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- W4367149210 title "Database for machine-learning research" @default.
- W4367149210 doi "https://doi.org/10.1021/cen-09944-scicon3" @default.
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