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Random forest classification models were trained on this data and assessed for prediction accuracy.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Results<\/jats:title>\n                <jats:p>The highest prediction accuracy of crystal shape was 93.5% assessed by fourfold cross-validation. When solvents were sequentially excluded from the training data, 32 out of 84 models predicted the shape of mefenamic acid crystals for the excluded solvent with 100% accuracy and a further 21 models had prediction accuracies from 50\u2013100%. Reducing the feature set to only solvent physical property descriptors and supersaturations resulted in higher overall prediction accuracies than the models trained using all available or another selected subset of molecular descriptors. For the 8 solvents on which the models performed poorly (&lt;\u200950% accuracy), further characterisation of crystals grown in these solvents resulted in the discovery of a new mefenamic acid solvate whereas all other crystals were the previously known form I.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Conclusions<\/jats:title>\n                <jats:p>Random forest classification models using solvent physical property descriptors can reliably predict crystal morphologies for mefenamic acid crystals grown in 20 out of the 28 solvents included in this work. Poor prediction accuracies for the remaining 8 solvents indicate that further factors will be required in the feature set to provide a more generalized predictive morphology model.<\/jats:p>\n              <\/jats:sec>","DOI":"10.1007\/s11095-022-03450-4","type":"journal-article","created":{"date-parts":[[2022,12,19]],"date-time":"2022-12-19T16:11:41Z","timestamp":1671466301000},"page":"3099-3111","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":19,"title":["Prediction of Mefenamic Acid Crystal Shape by Random Forest Classification"],"prefix":"10.1007","volume":"39","author":[{"given":"Siya","family":"Nakapraves","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Monika","family":"Warzecha","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chantal L.","family":"Mustoe","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Vijay","family":"Srirambhatla","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Alastair J.","family":"Florence","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,12,19]]},"reference":[{"issue":"2","key":"3450_CR1","doi-asserted-by":"publisher","first-page":"111","DOI":"10.1080\/00224065.2009.11917764","volume":"41","author":"JJ Peterson","year":"2009","unstructured":"Peterson JJ, Snee RD, McAllister PR, Schofield TL, Carella AJ. 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