The State of European Nursing Research: Dead, Alive, or Chronically Diseased? A Systematic Literature Review

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Abstract

Reviews of nursing research have suggested that most is descriptive; with no more than 15% providing strong evidence for practice. No studies have examined this from the perspective of nursing research conducted in Europe.

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Combining classifiers for robust PICO element detection

Florian Boudin, Jian-Yun Nie, Joan C Bartlett … (2010)

Background Formulating a clinical information need in terms of the four atomic parts which are Population/Problem, Intervention, Comparison and Outcome (known as PICO elements) facilitates searching for a precise answer within a large medical citation database. However, using PICO defined items in the information retrieval process requires a search engine to be able to detect and index PICO elements in the collection in order for the system to retrieve relevant documents. Methods In this study, we tested multiple supervised classification algorithms and their combinations for detecting PICO elements within medical abstracts. Using the structural descriptors that are embedded in some medical abstracts, we have automatically gathered large training/testing data sets for each PICO element. Results Combining multiple classifiers using a weighted linear combination of their prediction scores achieves promising results with an f-measure score of 86.3% for P, 67% for I and 56.6% for O. Conclusions Our experiments on the identification of PICO elements showed that the task is very challenging. Nevertheless, the performance achieved by our identification method is competitive with previously published results and shows that this task can be achieved with a high accuracy for the P element but lower ones for I and O elements.