Fuzzy queries aid in medical diagnosis

Authors

Keywords:

SQLf, fuzzy querying, automated medical diagnosis system

Abstract

This paper proposes the utilization of a fuzzy database engine for supporting medical diagnoses. Expert know how is stored in a relational database and then it is modeled diagnoses rules with fuzzy queries that pulls out the most accurate information related to the sickness and therefore supporting doctors with the medical diagnostic. A solution prototype has been developed with information related to respiratory disease characterization and it is built with fuzzy queries using SQLf. This case study can be used to define a roadmap for future developments in medical diagnosis supported on fuzzy databases. As always, the diagnosis can only be given by a specialist, these systems only provide help in their work task.

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Author Biographies

Josué Ramirez, Universidad Simón Bolivar, Venezuela

Ing. en Computación, MSc. en Computación.  Profesor contratado en la Universidad Simón Bolivar, Venezuela. Adscrito al Departamento de Computación y Tecnología de la Información. Correo: ramirezjosue@usb.ve

Leonid Tineo, Universidad Simón Bolivar, Venezuela

Ing. en Computación, MSc. en Computación, PhD en Computación, adscrito al Departamento de Computación y Tecnología de la Información de la Universidad Simón Bolivar, Venezuela. Correo: leonid@usb.ve

References

A.B. Bhattacharya, Arkajit Bhattacharya. Implementation of Fuzzy Technology in Complicated Medical Diagnostics and Further Decision. Fuzzy Expert Systems for Disease Diagnosis, p. 30, 2015

A.V. Senthil. Fuzzy Expert Systems for Disease Diagnosis, pages 400, 2014.

Edna Nuñez, Raul Vergara, José Bocanegra. Sistema experto basado en lógica difusa tipo 1 para determinar el grado de riesgo de preeclampsia. INGE CUC, pp.43-50, 2014.

Viridiana Cruz-Gutiérrez, Abraham Sánchez-López, A. Un sistema experto difuso en la Web para diagnóstico de diabetes. Research in Computing Science 107, pp. 145–155, 2015.

WH Xu, YL Chen, Z. Yan. Development of expert diagnostic system for common respiratory diseases. Journal of Zhejiang University. Medical sciences,43(2), pp.252-6, 2014.

Addis Lamesgin, M.Mohamed Sirajudeen. Implementation of an Expert System for Lung Disease Diagnosis, 2016.

Yutaka Hata, Osamu Ishikawa, Syoji Kobashi, K. Kondo, T. Nakano. Automated Medical Diagnosis System (AMDS) with Normal Degree based on fuzzy logic. Proceedings of Biomedical Engineering BioMED, Innsbruck, Austria. 2004.

Peter Innocent, Robert John. Computer aided fuzzy medical diagnosis. Information Sciences, Medical Expert Systems. Elseiver, 162(2): 81–104, 2004.

José Galindo. Introduction and Trends to Fuzzy Logic and Fuzzy Databases. In: Handbook of Research on Fuzzy Information Processing in Databases (Ed. José Galindo), Hershey, PA, USA: Information Science, 1-33, 2008.

Zongmin Ma, Li Yan. A Literature Overview of Fuzzy Conceptual Data Modeling. Journal of Information Science and Engineering, 26(2): 427-441, 2010.

Olivier Pivert, Patrick Bosc. Fuzzy Preference Queries to Relational Databases, Imperial College Press, London, 2012.

Earl Cox. Relational Database Queries using fuzzy logic. Artificial Intelligent Expert, 23-29, 1995.

Merriam-Webster, Medical Dictionary, Disponible: https://www.merriam-webster.com/ dictionary/#medicalDictionary.

C. Li, K. Chen-chuan, C. Ihab, F. Ilyas, S. Song. RankSQL: Query algebra and optimization for relational top-k queries. ACM SIGMOD International Conference on Management of Data, ACM Press, pages 131-142, June 14-16, 2005.

Stephan Börzsönyi, Donald Kossmann, Konrad Stocker. The Skyline operator. Proc. of 17th International Conf. on Data Engineering, pages 421-430, April 2-6, 2001.

José Galindo. New Characteristics in FSQL, a Fuzzy SQL for Fuzzy Databases. WSEAS International Conference on Artificial Intelligence, Knowledge Engineering Data Bases, pages 161-169, February 13-15, 2005.

Lotfi Zadeh. Fuzzy Sets. Information and Control, 8(3): 338-353, 1965.

Yosmar Lopez, Leonid Tineo: About the Performance of SQLf Evaluation Mechanisms. CLEI Electronic Journal. 9(2), 2006.

Didier Dubois, Henri Prade, Agnés Rico, Bruno Teheux. Generalized Sugeno Integrals. 16th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, June 20-24 2016.

MedicineNet, Inc, Available: http://www.medicinenet.com.

Ana Aguilera, Livia Borjas, Rosseline Rodríguez, Leonid Tineo. Experiences on fuzzy DBMS: Implementation and use. XXXIX Latin American Computing Conference, pages 478-485, October 7-11 2013.

Publicaciones en Ciencias y Tecnologia Vol 12 nro 2 año 20189

Published

2018-11-05

How to Cite

[1]
J. Ramirez and L. Tineo, “Fuzzy queries aid in medical diagnosis”, Publ.Cienc.Tecnol, vol. 12, no. 2, pp. 69-81, Nov. 2018.

Issue

Vol. 12 No. 2 (2018): July-December

Section

Research Article

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