Developing a Semantic Web Model for Medical Differential Diagnosis Recommendation | Journal of Medical Systems Skip to main content

Advertisement

Springer Nature Link
Log in

Developing a Semantic Web Model for Medical Differential Diagnosis Recommendation

  • Systems-Level Quality Improvement
  • Published:
Journal of Medical Systems Aims and scope Submit manuscript

Abstract

In this paper we describe a novel model for differential diagnosis designed to make recommendations by utilizing semantic web technologies. The model is a response to a number of requirements, ranging from incorporating essential clinical diagnostic semantics to the integration of data mining for the process of identifying candidate diseases that best explain a set of clinical features. We introduce two major components, which we find essential to the construction of an integral differential diagnosis recommendation model: the evidence-based recommender component and the proximity-based recommender component. Both approaches are driven by disease diagnosis ontologies designed specifically to enable the process of generating diagnostic recommendations. These ontologies are the disease symptom ontology and the patient ontology. The evidence-based diagnosis process develops dynamic rules based on standardized clinical pathways. The proximity–based component employs data mining to provide clinicians with diagnosis predictions, as well as generates new diagnosis rules from provided training datasets. This article describes the integration between these two components along with the developed diagnosis ontologies to form a novel medical differential diagnosis recommendation model. This article also provides test cases from the implementation of the overall model, which shows quite promising diagnostic recommendation results.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
¥17,985 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price includes VAT (Japan)

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13

Similar content being viewed by others

Notes

  1. http://www.w3.org/Submission/SWRL/

  2. http://www.genome.jp/kegg/pathway.html#global

  3. http://www.openclinical.org/medTermSnomedCT.html

  4. http://loinc.org/

  5. http://icd9cm.chrisendres.com/

  6. http://www.nlm.nih.gov/research/umls/

  7. http://do-wiki.nubic.northwestern.edu/index.php/Main_Page

  8. http://www.obofoundry.org/

  9. http://symptomontologywiki.igs.umaryland.edu/wiki/index.php/Main_Page

  10. http://en.wikipedia.org/wiki/Care_map

  11. http://www.jboss.org/drools

  12. http://www.cs.waikato.ac.nz/ml/weka/

  13. http://www.hcup-us.ahrq.gov/db/nation/nis/NIS_Introduction_2006.jsp

  14. http://www.cdc.gov/nchs/icd/icd9cm.htm

References

  1. Rodriguez, A., Mencke, M., Alor-Hernandez, G., Posada-Gomez, R., Gomez, J.M., Aguilar-Lasserre, A.A.: MEDBOLI: Medical Diagnosis Based on Ontologies and Logical Inference. In: IEEE International Conference on eHealth, Telemedicine, and Social Medicine, 2009, eTELEMED '09, Cancun, Mexico, Feb.1-7 (2009)

  2. Köhler, S., Schulz, MH., Krawitz, P., Bauer, S., Dölken, S., Ott, C.E., Mundlos, C., Horn, D., Mundlos, S., Robinson, P.N.: Clinical diagnostics in human genetics with semantic similarity searches in ontologies. In: Am J Hum Genet., 85 (4), pp. 457–464. October 9 (2009), http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2756558/?tool=pubmed

  3. Weiner, M., Pifer, E., Williams, V.: Computer-Aided Diagnosis. In: Encyclopedia of Biostatics, Published Online by John Wiley & Sons, 15 JUL (2005)

  4. Diamond, H., Clinical Reminder System: A Relational Database Application for Evidence-Based Medicine Practice, 2004.

    Google Scholar 

  5. Yeh, Y.C., Kuo, Y.H., Hsu, D.S.: Building expert systems by embedding analogical reasoning into deductive reasoning mechanism. In: Ninth Annual International Phoenix Conference on Computers and Communications, pp. 822 - 826. Scottsdale, AZ, USA, 21-23 March (1990)

  6. Wim, B.K., Wiegerinck, W., Akay, E., Neijt, J., Van Beek, A.: Promedas: A clinical diagnostic decision support system. In: Proceedings of the 15th Belgian-Dutch Conference on Artificial Intelligence (BNAIC), Netherlands (2003), http://www.kiranreddys.com/articles/clinicaldiagnosissupportsystems.pdf

  7. Matsumoto, T., Shimada, Y., Kawaji, S.: Clinical diagnosis support system based on symptoms and remarks by neural networks. In: 2004 I.E. Conference on Cybernetics and Intelligent Systems, pp. 1304 - 1307. Singapore (2004)

  8. Alexandrou, D. and Pardalis, K. V.: SEMantic PATHways: Modeling, Executing, and Monitoring Intra-Organizational Healthcare Business Processes towards Personalized Treatment”, In: e-Health Technologies and Improving Patient Safety: Exploring Organizational Factors, by Moumtzoglou A. and Kastania, A. N. edition, IGI Global Publisher, pp. 98-123, (2013).

  9. Hu, Z. Li, J.S., Zhou, T.S., Yu, H.Y.: Ontology-Based Clinical Pathways with Semantic Rules, In: Journal of Medical Systems , 36:4, pp.2203–2212, DOI: 10.1007/s10916-011-9687-0, (2012).

  10. Alexandrou, D., Xenikoudakis, F., Mentzas, G., SEMPATH: Semantic Adaptive and Personalized Clinical Pathways. In: eTELEMED '09, International Conference on eHealth, Telemedicine, and Social Medicine, pp. 36 – 41. Cancun, Mexico 1-7 Feb. (2009)

  11. Alexandrou, D., Xenikoudakis, F., and Mentzas, G., Adaptive Clinical Pathways with Semantic Web Rules. In: IEEE International Conference on Health Informatics, Madeira, Portugal 28–31(January), 2008.

  12. Chabalier, J., Dameron, O., Burgun, A.: Integrating and querying disease and pathway ontologies: building an OWL model and using RDFS queries. In: The 10th Annual Bio-Ontologies Meeting, Co-Located with ISMB/ECCB 2007, Austria, July (2007), http://www.ea3888.univ-rennes1.fr/lim/doc_184.pdf

  13. 13. Ye, Y., Jiang, Z., Yang, D., Du, G.: A semantics-based clinical pathway workflow and variance management framework. In: IEEE Intl. Conf. on Service Operations and Logistics, and Informatics, pp. 758-763. Beijing, China, IEEE Press (2008)

  14. Chen, H., Colaert, D., De Roo, J.: Towards Adaptable Clinical Pathway Using Semantic Web Technology. In: W3C Workshop Semantic Web for Life Science, Position Paper, July (2004), http://www.w3.org/2004/07/swls-cfp.html

  15. Chen, H.: Semantic Web in Adaptable Health Care Protocols and Pathways Group Charter - A proposal. February (2006), http://www.w3.org/2001/sw/hcls/task_forces/AHPP_Task_Force.doc

  16. Popescu, M., Khalilia, M.: Improving disease prediction using ICD-9 ontological features. In: 2011 I.E. International Conference on Fuzzy Systems, pp.1805-1809. Taipei, Taiwan, 27-30 June (2011)

  17. Ye, Y., Jiang, Z., Diao, X., Yang, D., and Du, G., An ontology-based hierarchical semantic modeling approach to clinical pathway workflows. In: Computers in Biology and Medicine 39(8):722–732, 2009.

    Google Scholar 

  18. Lin, Y. C.: Development of an Ontology-based Flexible Clinical Pathway System. In: WSEAS Transactions on Information Science and Applications, 6 (12), (2009), http://www.wseas.us/e-library/transactions/information/2009/32-900.pdf

  19. Hu, Z., Li, J. S., Zhou, T. S., Yu, H. Y., Suzuki, M., and Araki, K., Ontology-Based Clinical Pathways with Semantic Rules. J Med Syst, Springe, 2011.

  20. Huang, Z., Lu, X., Duang, H.: Using Recommendation to Support Adaptive Clinical Pathways, In: Journal of Medical Systems, 36:3, pp.1849–1860, DOI: 10.1007/s10916-010-9644-3, (2012)

  21. Martínez-Pérez, B., and Torre-Díez, I., Mobile Clinical Decision Support Systems and Applications: A Literature and Commercial Review. In: Journal of Medical Systems 38:4, 2014. doi:10.1007/s10916-013-0004-y.

    Google Scholar 

  22. Hurley, K.F., Abidi, S.S.R.: Ontology Engineering to Model Clinical Pathways: Towards the Computerization and Execution of Clinical Pathways, In: Proc of the 20th IEEE Int. Symposium on Computer-based Medical Systems, pp. 536-541, 20-22 June 2007, Maribor, Slovenia, (2007)

  23. Shen, C.P., Jigjidsuren, C., Dorjgochoo, S: A Data-Mining Framework for Transnational Healthcare System, In: Journal of Medical Systems, 36:4, pp.2565–2575, DOI 10.1007/s10916-011-9729-7, (2012)

  24. Jalali,V., Borujerdi, M.R.M.: A Unified Architecture for Biomedical Search Engines Based on Semantic Web Technologies, In: Journal of Medical Systems, 35:2, pp.237–249, DOI: 10.1007/s10916-009-9360-z, (2011)

  25. Scheuermann, R. H., Werner, C., Smith, B.: Toward an Ontological Treatment of Disease and Diagnosis. In: Proceedings of the 2009 AMIA Summit on Translational Bioinformatics, pp. 116-120. San Francisco, CA, (2009), http://ontology.buffalo.edu/medo/Disease_and_Diagnosis.pdf

  26. Hamm, R., Knoop, S.E., Schwarz, P., Block, A.D., Davis, W.L.: Harmonizing clinical terminologies: driving interoperability in healthcare. In: Loinic Stud Health Technol Inform Report No. 129:660-3, (2007), http://loinc.org/articles/Hamm2007a

  27. Liu, R. L., Tung, S. Y., and Lu, Y. L., Identifying Disease Diagnosis Factors by Proximity-Based Mining of Medical Texts, In Intelligent Information and Database Systems. Lecture Notes in Computer Science (LNCS) 6592:171–180, 2011.

    Article  Google Scholar 

  28. Mohammed, O., and Benlamri, R., Building a Diseases Symptoms Ontology for Medical Diagnosis. In: An Integrative Approach, IEEE International Conference on Future Generation Communication Technology, British Computer Society, London, 2012.

    Google Scholar 

  29. Mohammed, O.: “Semantic Web System for Differential Diagnosis Recommendations”. MSc Thesis, Supervised By: Prof. Dr. Rachid Benlamri, Lakehead University, (2012)

  30. Hughes, T.C., Ashpole, B.C.: The Semantics of Ontology Alignment. In: I3CO Information Interpretation and Integration Conference, (2004), http://www.atl.lmco.com/projects/ontology/papers/SOA.pdf

  31. Zhang, S., Bodenreider, O.: Alignment of multiple ontologies of anatomy: deriving indirect mappings from direct mappings to a reference. In: Proceedings for AMIA Annual Symposium, Washington, DC (2005), http://www.lhncbc.nlm.nih.gov/lhc/docs/published/2005/pub2005039.pdf

  32. Doan, A.H. et al: Learning to match ontologies on the Semantic Web. In: The VLDB Journal — The International Journal on Very Large Data Bases archive, vol. 12, issue 4. November (2003)

  33. Homola, M., Serafini, L.: Towards Formal Comparison of Ontology Linking, Mapping and Importing. In: Proceeding of 23rd Int. Workshop on Description Logics (DL2010), CEUR-WS 573, Waterloo, Canada (2010), http://www.cs.uwaterloo.ca/conferences/dl2010/papers/paper_26.pdf

  34. http://flash.lakeheadu.ca/~omohamme/DSO1.owl

  35. http://flash.lakeheadu.ca/~omohamme/PatientOntology.owl

  36. Victoria Dept. of Health: Pathways for Prediabetes, Type 1, Type 2 and Gestational Diabetes. Department of Health - Loddon Mallee Region, Victoria, Australia (2009)

  37. National Institute for Health and Clinical Excellence (NHS): Hypertension: management of hypertension in adults in primary care, August (2004)

  38. Goodnough et al: Detection, Evaluation, and Management of Anemia in the Elective Surgical Patient. In: The International Anesthesia Research Society, (2005)

  39. Famili, A., Ouyang, J.: Data Mining: Understanding Data and Disease Modeling. In: Proceedings of IASTED-AI-03 Conference. Innsbruck, Austria, February 10-13 (2003)

Download references

Author information

Authors and Affiliations

  1. Department of Software Engineering, Lakehead University, 955 Oliver Road, Thunder Bay, P7B 5E1, ON, Canada

    Osama Mohammed & Rachid Benlamri

Authors
  1. Osama Mohammed
    View author publications

    You can also search for this author inPubMed Google Scholar

  2. Rachid Benlamri
    View author publications

    You can also search for this author inPubMed Google Scholar

Corresponding author

Correspondence to Osama Mohammed.

Additional information

This article is part of the Topical Collection on Systems-Level Quality Improvement

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Mohammed, O., Benlamri, R. Developing a Semantic Web Model for Medical Differential Diagnosis Recommendation. J Med Syst 38, 79 (2014). https://doi.org/10.1007/s10916-014-0079-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s10916-014-0079-0

Keywords