Extracting information from free text through unsupervised graph-based clustering: an application to patient incident records

The large volume of text in electronic healthcare records often remains underused due to a lack of methodologies to extract interpretable content. Here we present an unsupervised framework for the analysis of free text that combines text-embedding with paragraph vectors and graph-theoretical multisc...

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Bibliographische Detailangaben

Hauptverfasser:	Altuncu, M. Tarik, Sorin, Eloise, Symons, Joshua D, Mayer, Erik, Yaliraki, Sophia N, Toni, Francesca, Barahona, Mauricio
Format:	Artikel
Sprache:	eng
Schlagworte:	Computer Science - Computation and Language Computer Science - Information Retrieval Computer Science - Learning Mathematics - Spectral Theory Statistics - Machine Learning
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