Validation and Calibration of Dietary Intake in Chronic Kidney Disease: An Ontological Approach

  • Yu-Liang Chi
  • Tsang-Yao Chen
  • Wan-Ting Tsai
Conference paper
Part of the Lecture Notes in Business Information Processing book series (LNBIP, volume 208)


This study develops a pilot knowledge-based system (KBS) for addressing validation and calibration of dietary intake in chronic kidney disease (CKD). The system is constructed by using Web Ontology Language (OWL) and Semantic Web Rule Language (SWRL) to demonstrate how a KBS approach can achieve sound problem solving modeling and effective knowledge inference. In terms of experimental evaluation, data from 36 case patients are used for testing. The evaluation results show that, excluding the interference factors and certain non-medical reasons, the system has achieved the research goal of CKD dietary consultation. For future studies, the problem solving scope can be expanded to implement a more comprehensive dietary consultation system.


Knowledge-based system Chronic kidney disease Ontology Semantic rules 



The authors would like to thank the National Science Council of the Republic of China, Taiwan for financially supporting this research under Contract No. NSC 102-2410-H-033-036-MY2.


  1. 1.
  2. 2.
    McCullough, M.L., Feskanich, D., Stampfer, M.J., Giovannucci, E.L., Rimm, E.B., Hu, F.B., et al.: Diet quality and major chronic disease risk in men and women, moving toward improved dietary guidance. Am. J. Clin. Nutr. 76, 1261–1271 (2002)Google Scholar
  3. 3.
    Levey, A.S., Coresh, J., Balk, E., Kausz, A.T., Levin, A., Steffes, M.W., et al.: National kidney foundation practice guidelines for chronic kidney disease, evaluation, classification, and stratification. Ann. Intern. Med. 139, 137–147 (2003)CrossRefGoogle Scholar
  4. 4.
    Kalista-Richards, M.: The kidney, medical nutrition therapy—yesterday and today. Nutr. Clin. Pract. 26, 143–150 (2011)CrossRefGoogle Scholar
  5. 5.
    Myers, G.L., Miller, W.G., Coresh, J., Fleming, J., Greenberg, N., Greene, T., et al.: Recommendations for improving serum creatinine measurement, a report from the laboratory working group of the national kidney disease education program. Clin. chem. 52, 5–18 (2006)CrossRefGoogle Scholar
  6. 6.
    Stevens, L.A., Coresh, J., Greene, T., Levey, A.S.: Assessing kidney function — measured and estimated glomerular filtration rate. N. Engl. J. Med. 354, 2473–2483 (2006)CrossRefGoogle Scholar
  7. 7.
    Plessers, P., De Troyer, O., Casteleyn, S.: Understanding ontology evolution, a change detection approach. Web Semant. Sci. Serv. Agents World Wide Web. 5, 39–49 (2007)CrossRefGoogle Scholar
  8. 8.
    Welty, C., Guarino, N.: Supporting ontological analysis of taxonomic relationships. Data Knowl. Eng. 39, 51–74 (2001)zbMATHCrossRefGoogle Scholar
  9. 9.
    García-Castro, R., Gómez-Pérez, A.: Interoperability results for semantic web technologies using OWL as the interchange language. Web Semant. Sci. Serv. Agents World Wide Web. 8, 278–291 (2010)CrossRefGoogle Scholar
  10. 10.
    Horrocks, I., Patel-Schneider, P.F., van Harmelen, F.: From SHIQ and RDF to OWL, the making of a web ontology language. Web Semant. Sci. Serv. Agents World Wide Web. 1, 7–26 (2003)CrossRefGoogle Scholar
  11. 11.
    Gennari, J.H., Musen, M.A., Fergerson, R.W., Grosso, W.E., Crubézy, M., Eriksson, H., et al.: The evolution of Protégé, an environment for knowledge-based systems development. Int. J. Hum. Comput Stud. 58, 89–123 (2003)CrossRefGoogle Scholar
  12. 12.
    Corsar, D., Sleeman, D.: Reusing jesstab rules in Protégé. Knowl.-Based Syst. 19, 291–297 (2006)CrossRefGoogle Scholar
  13. 13.
    Horrocks, I., Patelschneider, P., Bechhofer, S., Tsarkov, D.: OWL rules, a proposal and prototype implementation. Web Semant. Sci. Serv. Agents World Wide Web. 3, 23–40 (2005)CrossRefGoogle Scholar
  14. 14.
    Gómez-Pérez, A., Benjamins, V.R.: Applications of ontologies and problem-solving methods. AI Mag. 20, 119–122 (2009)Google Scholar
  15. 15.
    Fernández-López, M., Gómez-Pérez, A., Suárez-Figueroa, M.C.: Methodological guidelines for reusing general ontologies. Data Knowl. Eng. 86, 242–275 (2013)CrossRefGoogle Scholar
  16. 16.
    Fürst, F., Trichet, F.: Integrating domain ontologies into knowledge-based systems. In: Proceedings of the Eighteenth International Florida Artificial Intelligence Research Society Conference, pp. 826–827 (2005)Google Scholar
  17. 17.
    Chen, Y., Hsu, C.-Y., Liu, L., Yang, S.: Constructing a nutrition diagnosis expert system. Expert Syst. Appl. 39, 2132–2156 (2012)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Department of Information ManagementChung Yuan Christian UniversityChung-LiTaiwan
  2. 2.Department of Management Information SystemsNational Chengchi UniversityTaipei CityTaiwan

Personalised recommendations