Predicting Publication of Clinical Trials Using Structured and Unstructured Data: Model Development and Validation Study.

Different factors affect the publication of a registered clinical trial. Our approach to predictive modeling combines heterogeneous features, both structured and unstructured. We show that methods from natural language processing can provide effective textual features to enable more accurate prediction of publication success, which has not been explored for this task previously.