Improving Medical Information Retrieval with PICO Element Detection
| Titre | Improving Medical Information Retrieval with PICO Element Detection |
| Type de publication | Conference Paper |
| Année de publication | 2010 |
| Auteurs | Boudin, F., L. Shi, and J-Y. Nie |
| Nom de la conférence | Proceedings of the ECIR 2010 Conference |
| Mots-clés | health, ir, pico |
| Résumé | Without a well formulated and structured question, it can be very difficult and time consuming for physicians to identify appro- priate resources and search for the best available evidence for medical treatment in evidence-based medicine ({EBM}). In {EBM}, clinical studies and questions involve four aspects: {Population/Problem} (P), Interven- tion (I), Comparison (C) and Outcome (O), which are known as {PICO} elements. It is intuitively more advantageous to use these elements in Information Retrieval ({IR}). In this paper, we first propose an approach to automatically identify the {PICO} elements in documents and queries. We test several possible approaches to use the identified elements in {IR}. Experiments show that it is a challenging task to determine accurately {PICO} elements. However, even with noisy tagging results, we can still take advantage of some {PICO} elements, namely I and P elements, to enhance the retrieval process, and this allows us to obtain significantly better retrieval effectiveness than the state-of-the-art methods. |
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