Fuzzy queries aid in medical diagnosis

Publicaciones en Ciencias y Tecnología

View Publication Info
 
 
Field Value
 
Title Fuzzy queries aid in medical diagnosis
Consultas difusas en asistencia al diagnóstico médico
 
Creator Ramirez, Josué
Tineo, Leonid
 
Description 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.
Este artículo propone el uso de un motor de base de datos difuso para ayudar en el diagnóstico médico. El conocimiento experto se almacena en una base de datos relacional y luego se modela mediante reglas de diagnóstico con consultas difusa que extraen la información más precisa relacionada con la enfermedad y, por lo tanto, apoyan a los médicos con el diagnóstico médico. Hemos construido un prototipo de sistema con una base de datos que almacena la caracterización de enfermedades respiratorias. Esta aplicación se ha creado utilizando un sistema de gestión de bases de datos que admite el lenguaje de consulta difusa SQLf. Este trabajo encamina desarrollos futuros en el diagnóstico médico soportado sobre bases de datos difusas. Como siempre, el diagnóstico solo puede ser dado por un especialista, estos sistemas solo brindan ayuda en su labor médica.
 
Publisher Universidad Centroccidental Lisandro Alvarado
 
Date 2018-11-05
 
Type info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Research article
Artículo de investigación original
 
Format application/pdf
 
Identifier https://revistas.ucla.edu.ve/index.php/pcyt/article/view/1397
 
Source Publicaciones en Ciencias y Tecnología; Vol 12 No 2 (2018): July-December; 69-81
Publicaciones en Ciencias y Tecnología; Vol. 12 Núm. 2 (2018): Julio-Diciembre; 69-81
Publicaciones en Ciencias y Tecnología; v. 12 n. 2 (2018): Julio-Diciembre; 69-81
2477-9660
1856-8890
 
Language eng
 
Relation https://revistas.ucla.edu.ve/index.php/pcyt/article/view/1397/1050
/*ref*/A.B. Bhattacharya; A.Bhattacharya. Implementation of fuzzy technology in complicated medical diagnostics and further decision, pages 935–968. IGI Global, 02 2017.
/*ref*/A.V. Senthil Kumar. Fuzzy expert systems for disease diagnosis. Advances in Medical Technologies and Clinical Practice:. IGI Global, 2014. OnLine.
/*ref*/E. Núñez Flórez; R.Vergara Ortiz; J. Bocanegra García. Sistema experto basado en lógica difusa tipo 1 para determinar el grado de riesgo de preeclampsia. INGE CUC, 10(1):43–50, 2014. OnLine.
/*ref*/V. Cruz-Gutiérrez; A.S. López. Un sistema experto difuso en la web para diagnóstico de diabetes. Research in Computing Science, 107:145–155, 2015.
/*ref*/W.H. Xu; Y. L. Chen; Z. Yan. Development of expert diagnostic system for common respiratory diseases. Zhejiang da xue xue bao. Yi xue ban=Journal of Zhejiang University. Medical sciences, 43(2):252–256, 2014.
/*ref*/A. Lamesgin; M. M Sirajudeen. Implementation of an expert system for Lung disease diagnosis. Disponible: https://www.researchgate.net.
/*ref*/Y. Hata; O. Ishikawa; S. Kobashi; K. Kondo; T. Nakano. Automated medical diagnosis system (amds) with normal degree based on fuzzy logic. In Proc. 2nd IASTED Int. Conf. on Biomedical Engineering, pages 590–593, 2004.
/*ref*/P. R. Innocent; R. I. John. Computer aided fuzzy medical diagnosis. Information Sciences. Medical Expert Systems. Elseiver, 162(2):81–104, 2004.
/*ref*/J. Galindo. Introduction and trends to fuzzy logic and fuzzy databases. In Handbook of Research on Fuzzy Information Processing in Databases, pages 1–33. IGI Global, 2008.
/*ref*/Z. M. Ma; L. Yan. A literature overview of fuzzy conceptual data modeling. J. Inf. Sci. Eng., 26(2):427–441, 2010.
/*ref*/O. Pivert; P. Bosc. Fuzzy preference queries to relational databases. Imperial College Press, London, 2012.
/*ref*/E. Cox. Relational database queries using fuzzy logic. AI Expert, 10(1):22–29, 1995.
/*ref*/Merriam-Webster. Medical Dictionary. OnLine. [14] C. Li; K. C. Chang; I. F. Ilyas; S. Song. RankSQL: query algebra and optimization for relational top-k queries. In Proceedings of the 2005 ACM SIGMOD international conference on Management of data, pages 131–142. ACM, 2005.
/*ref*/S. Borzsony; D. Kossmann; K. Stocker. The skyline operator. In 17th IEEE International Conference on Data Engineering, pages 421–430. IEEE, 2001.
/*ref*/L. Galindo. New characteristics in FSQL, a fuzzy SQL for fuzzy databases. WSEAS Transactions on Information Science and Applications, 2(2):161–169, 2005.
/*ref*/L. A. Zadeh. Fuzzy sets. Information and control, 8:338–353, 1965. OnLine.
/*ref*/Y. López; L. Tineo. About the performance of sqlf evaluation mechanisms. CLEI Electronic Journal, 9(2):8–1, 2006.
/*ref*/D. Dubois; H. Prade; A. Rico; B. Teheux. Generalized sugeno integrals. In International Conference on Information Processing andManagement of Uncertainty in Knowledge-Based Systems, pages 363–374. Springer, 2016.
/*ref*/Inc MedicineNet. MedicineNet, Inc. OnLine.
/*ref*/A. I. Aguilera; L. Borjas; R. Rodriguez; L. Tineo. Experiences on fuzzy DBMS: Implementation and use. In XXXIX Latin American Computing Conference, 2013.
 

Contact Us

The PKP Index is an initiative of the Public Knowledge Project.

For PKP Publishing Services please use the PKP|PS contact form.

For support with PKP software we encourage users to consult our wiki for documentation and search our support forums.

For any other correspondence feel free to contact us using the PKP contact form.

Find Us

Twitter

Copyright © 2015-2018 Simon Fraser University Library