Abstract
Summarizing the evidence about medical interventions is an immense undertaking, in part because unstructured Portable Document Format (PDF) documents remain the main vehicle for disseminating scientific findings. Clinicians and researchers must therefore manually extract and synthesise information from these PDFs. We introduce Spá1,2 a web-based viewer that enables automated annotation and summarisation of PDFs via machine learning. To illustrate its functionality, we use Spá to semi-automate the assessment of bias in clinical trials. Spá has a modular architecture, therefore the tool may be widely useful in other domains with a PDF-based literature, including law, physics, and biology
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Kuiper, J., Marshall, I.J., Wallace, B.C., Swertz, M.A. (2014). Spá: A Web-Based Viewer for Text Mining in Evidence Based Medicine. In: Calders, T., Esposito, F., Hüllermeier, E., Meo, R. (eds) Machine Learning and Knowledge Discovery in Databases. ECML PKDD 2014. Lecture Notes in Computer Science(), vol 8726. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-44845-8_33
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DOI: https://doi.org/10.1007/978-3-662-44845-8_33
Publisher Name: Springer, Berlin, Heidelberg
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