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A Study of an Automatic Stopping Strategy for Technologically Assisted Medical Reviews

  • Giorgio Maria Di Nunzio
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10772)

Abstract

Systematic medical reviews are a method to collect the findings from multiple studies in a reliable way. Given budget and time constraints, limiting the recall of a search may undermine the quality of a review to such a degree that the validity of its findings is questionable. In this paper, we investigate a variable threshold approach to tackle the problem of a total recall task in medical reviews proposed by a Cross-Language Evaluation Forum (CLEF) eHealth lab in 2017. Compared to the official results submitted to the CLEF eHealth task, our approach performed consistently better over all the range of thresholds considered achieving a recall greater than 0.95 with 25,000 documents less than the best performing systems. The runs and the source code to generate the analyses of this paper are available at the following GitHub repository (https://github.com/gmdn/ECIR2018).

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Information EngineeringUniversity of PaduaPaduaItaly

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