A Topic-centric Approach to Detecting New Evidences for Evidence-based Medical Guidelines

Qing Hu, Zhisheng Huang, Annette ten Teije, Frank van Harmelen, M. Scott Marshall, Andre Dekker

Abstract

Evidence-based Medical guidelines are developed based on the best available evidence in biomedical science and clinical practice. Such evidence-based medical guidelines should be regularly updated, so that they can optimally serve medical practice by using the latest evidence from medical research. The usual approach to detect such new evidence is to use a set of terms from a guideline recommendation and to create queries for a biomedical search engine such as PubMed, with a ranking over a selected subset of terms to search for relevant new evidence. However, the terms that appear in a guideline recommendation do not always cover all of the information we need for the search, because the contextual information (e.g. time and location, user profile, topics) is usually missing in a guideline recommendation. Enhancing the search terms with contextual information would improve the quality of the search results. In this paper, we propose a topic-centric approach to detect new evidence for updating evidence-based medical guidelines as a context-aware method to improve the search. Our experiments show that this topic centric approach can find the goal evidence for 12 guideline statements out of 16 in our test set, compared with only 5 guideline statements that were found by using a non-topic centric approach.

References

  1. Ait-Mokhtar, S., Bruijn, B. D., Hagege, C., and Rupi, P. (2013). Initial prototype for relation identification between concepts, D3.2. Technical report, EURECA Project.
  2. Aït-Mokhtar, S., Chanod, J.-P., and Roux, C. (2002). Robustness beyond shallowness: incremental deep parsing. Natural Language Engineering, 8(2):121-144.
  3. Cilibrasi, R. and M.B.Vitanyi, P. (2007). The google similarity distance. IEEE Trans. Knowledge and Data Engineering, 19:370-383.
  4. Hu, Q., Huang, Z., den Teije, A., and van Harmelen, F. (2015). Detecting new evidence for evidence-based guidelines using a semantic distance method. In Proceedings of the 15th Conference on Artificial Intelligence in Medicine(AIME 2015).
  5. Hu, Q., Huang, Z., van Harmelen, F., ten Teije, A., and Gu, J. (2014). Evidence-based clinical guidelines in SemanticCT. In The Semantic Web and Web Science, Volume 480 of the series Communications in Computer and Information Science, pages 198-212. Springer.
  6. Huang, Z., ten Teije, A., and van Harmelen, F. (2013). SemanticCT: A semantically enabled clinical trial system. In Lenz et al., R., editor, Process Support and Knowledge Representation in Health Care. Springer LNAI.
  7. Huang, Z., ten Teije, A., van Harmelen, F., and AitMokhtar, S. (2014). Semantic representation of evidence-based clinical guidelines. In Proceedings of 6th International Workshop on Knowledge Representation for Health Care (KR4HC'14).
  8. Iruetaguena et al, A. (2013). Automatic retrieval of current evidence to support update of bibliography in clinical guidelines. Expert Sys with Apps, 40:2081-2091.
  9. NABON (2004). Guideline for the treatment of breast carcinoma 2004. Technical report, Nationaal Borstkanker Overleg Nederland (NABON).
  10. NABON (2012). Breast cancer, dutch guideline, version 2.0. Technical report, Integraal kankercentrum Netherland, Nationaal Borstkanker Overleg Nederland.
  11. NSRS (2006). Guideline complex regional pain syndrome type i. Technical report, Netherlands Society of Rehabilitation Specialists.
  12. Reinders, R., ten Teije, A., and Huang, Z. (2015). Finding evidence for updates in medical guideline. In Proceedings of HEALTHINF2015. Lisbon.
  13. Stalnaker, R. (1999). Context and content. Oxford: Oxford University Press.
  14. Woolf, S., Grol, R., Hutchinson, A., Eccles, M., and Grimshaw, J. (1999). Clinical guidelines:potential benefits, limitations, and harms of clinical guidelines. BMJ, 318(7182):527-530.
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Paper Citation


in Harvard Style

Hu Q., Huang Z., Teije A., Harmelen F., Marshall M. and Dekker A. (2016). A Topic-centric Approach to Detecting New Evidences for Evidence-based Medical Guidelines . In Proceedings of the 9th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 5: HEALTHINF, (BIOSTEC 2016) ISBN 978-989-758-170-0, pages 282-289. DOI: 10.5220/0005698902820289


in Bibtex Style

@conference{healthinf16,
author={Qing Hu and Zhisheng Huang and Annette ten Teije and Frank van Harmelen and M. Scott Marshall and Andre Dekker},
title={A Topic-centric Approach to Detecting New Evidences for Evidence-based Medical Guidelines},
booktitle={Proceedings of the 9th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 5: HEALTHINF, (BIOSTEC 2016)},
year={2016},
pages={282-289},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005698902820289},
isbn={978-989-758-170-0},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 9th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 5: HEALTHINF, (BIOSTEC 2016)
TI - A Topic-centric Approach to Detecting New Evidences for Evidence-based Medical Guidelines
SN - 978-989-758-170-0
AU - Hu Q.
AU - Huang Z.
AU - Teije A.
AU - Harmelen F.
AU - Marshall M.
AU - Dekker A.
PY - 2016
SP - 282
EP - 289
DO - 10.5220/0005698902820289