3 papers
cs.LG2019
Extracting information from free text through unsupervised graph-based clustering: an application to patient incident records
M. Tarik Altuncu, Eloise Sorin, Joshua D. Symons +4
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 f…
cs.CL2018
From Free Text to Clusters of Content in Health Records: An Unsupervised Graph Partitioning Approach
M. Tarik Altuncu, Erik Mayer, Sophia N. Yaliraki +1
Electronic Healthcare records contain large volumes of unstructured data in different forms. Free text constitutes a large portion of such data, yet this source of richly detailed…
cs.CL2018
From Text to Topics in Healthcare Records: An Unsupervised Graph Partitioning Methodology
M. Tarik Altuncu, Erik Mayer, Sophia N. Yaliraki +1
Electronic Healthcare Records contain large volumes of unstructured data, including extensive free text. Yet this source of detailed information often remains under-used because of…