3 research outputs found

    LIMSI@CLEF eHealth 2017 Task 2: Logistic Regression for Automatic Article Ranking

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    This paper describes the participation of the LIMSI-MIROR team at CLEF eHealth 2017, task 2. The task addresses the automatic ranking of articles in order to assist with the screening process of Diagnostic Test Accuracy (DTA) Systematic Reviews. We used a logistic regression classifier and handled class imbalance using a combination of class reweighting and undersampling. We also experimented with two strategies for relevance feedback. Our best run obtained an overall Average Precision of 0.179 and Work Saved over Sampling @95% Recall of 0.650. This run uses stochastic gradient descent for training but no feature selection or relevance feedback. We observe high performance variation within the queries in the test set. Nonetheless, our results suggest that automatic assistance is promising for ranking the DTA literature as it could reduce the screening workload for review writer by 65% on average

    Search strategy formulation for systematic reviews: Issues, challenges and opportunities

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    Systematic literature reviews play a vital role in identifying the best available evidence for health and social care research, policy, and practice. The resources required to produce systematic reviews can be significant, and a key to the success of any review is the search strategy used to identify relevant literature. However, the methods used to construct search strategies can be complex, time consuming, resource intensive and error prone. In this review, we examine the state of the art in resolving complex structured information needs, focusing primarily on the healthcare context. We analyse the literature to identify key challenges and issues and explore appropriate solutions and workarounds. From this analysis we propose a way forward to facilitate trust and to aid explainability and transparency, reproducibility and replicability through a set of key design principles for tools to support the development of search strategies in systematic literature reviews
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