Abstract
The research presents the expert system for diagnosing the risk from urine tests by collecting diagnostic information from documents, books, experts, and the results of urine tests. The sample was 9,961 to create knowledge under decision tree technique. The result of the study was shown that the systems could approximately diagnose the risk of 12 types of disease, including diabetes, infected, gallstone, tumor, bladder inflammation, urological disorders, kidney disease, SLE, jaundice, G6PD deficiency, infectious disease, and diabetes insipidus. Also, the model gained from the creation of determinability tree in diagnosing the diseases created 96 IF-THEN Rules that used the strategy of forward chaining inferences in diagnosing the risk.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Kitporntheranunt, M., Wiriyasuttiwong, W.: Development of a medical expert system for the diagnosis of ectopic pregnancy. J. Med. Assoc. Thai. 93(Suppl 2), S43–S49 (2010)
Kumar, D.S., Sathyadevi, G., Sivanesh, S.: Decision support system for medical diagnosis using data mining. Int. J. Comput. Sci. Issues 8(Issue 3, No. 1), 147–153 (2011)
Buchanan, B.G., Shortliffe, E.H.: Rule Based Expert Systems: The Mycin Experiments of the Stanford Heuristic Programming Project (The Addison-Wesley Series in Artificial Intelligence). Addison-Wesley Longman Publishing Co., Inc., Reading, MA, USA (1984)
Majali, J., Niranjan, R., Phatak, V., Tadakhe, O.: Int. J. Comput. Sci. Inf. Technol. (IJCSIT) 5, 6487–6490 (2014)
Fayyad, U.M., Pitatesky-Shapiro, G., Smyth, P., Uthurasamy, R.: Advances in Knowledge Discovery and Data Mining. AAAI/MIT Press (1996)
Tama, B.A., Rodiyatul, F.S., Hermansyah: An early detection method of Type-2 diabetes mellitus in public hospital. In: Proceeding of the International Conference on Informatics, Cybernetic, and Computer Applications. Bangalore, vol. 9, no. 2, pp. 287–294 (2010)
Chen, T.C., Hsu, T.C.: A GAs based approach for mining breast cancer pattern. Expert Syst. Appl. 30, 674–681 (2006)
Tomar, P.P., Singh, R., Saxena, P.K.: A medical multimedia based clinical decision support system for operational chronic lung diseases diagnosis and training. Int. J. Comput. Appl. 49(8), 1–12 (2012)
Joshi, J., Doshi, R., Patel, J.: Diagnosis and prognosis breast cancer using classification rules. Int. J. Eng. Res. General Sci. 2, 315–323 (2014)
Kularbphettong, K., Waraporn, P., Tongsiri, C.: Analysis of student motivation behavior on e-learning based on association rule mining. World Acad. Sci. Eng. Technol. (2012)
Topaloğlu, M., Malkoç, G.: Decision tree application for renal calculi diagnosis. Int. J. Appl. Math. Electron. Comput. Special Issue, 404–407 (2016)
Edelstein, H.: Introduction to Data Mining and Knowledge Discovery, 3rd edn. Two Crows Corporation, Potomac, MD, USA (1999)
Azar, A.T., El-Metwally, S.M.: Decision tree classifiers for automated medical diagnosis. Neural Comput. Appl. (2013)
Azar, A.T., El-Metwally, S.M.: Decision tree classifiers for automated medical diagnosis. Neural Comput. Appl. 23(7–8), 2387–2403 (2012)
Chen, C., He, B., Zeng, Z.: A method for mineral prospectivity mapping integrating C4.5 decision tree, weights-of-evidence and m-branch smoothing techniques: a case study in the eastern Kunlun Mountains, China. Earth Sci. Inform. (2014)
Acknowledgements
The authors would like to be grateful to the financial subsidy provided by Suan Sunandha Rajabhat University, and we would like to acknowledge friends and family.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Tachpetpaiboon, N., Kularbphettong, K., Janpla, S. (2019). Expert System for Diagnosing Disease Risk from Urine Tests. In: Bhatia, S., Tiwari, S., Mishra, K., Trivedi, M. (eds) Advances in Computer Communication and Computational Sciences. Advances in Intelligent Systems and Computing, vol 760. Springer, Singapore. https://doi.org/10.1007/978-981-13-0344-9_20
Download citation
DOI: https://doi.org/10.1007/978-981-13-0344-9_20
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-13-0343-2
Online ISBN: 978-981-13-0344-9
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)