Assessment of machine learning approaches for predicting the crystallization propensity of active pharmaceutical ingredients
CrystEngComm2018Vol. 21(8), pp. 1215–1223
Citations Over TimeTop 20% of 2018 papers
Ayana Ghosh, Lydie Louis, Kapildev K. Arora, Bruno C. Hancock, Joseph F. Krzyzaniak, Paul Meenan, Serge Nakhmanson, Geoffrey P. F. Wood
Abstract
This work critically evaluates a number of machine learning approaches for predicting the crystallization propensity of active pharmaceutical ingredients using a real-world dataset.
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