Case based expert system for hypertension diagnosis
DOI:
https://doi.org/10.17533/udea.redin.13748Keywords:
sistema experto basado en casos, hipertensión arterial, técnicas estadísticasAbstract
This paper describes a case based expert system for hypertension diagnosis in Santa Clara city, Cuba, carried out as part of an investigation to know the incidence of the disease in this population.
The studied population’s sample was formed by 455 men and 394 women, with ages between 18 and 78 years. The cases were classified in three groups: normal (people with normal blood pressure), with prehypertension (people that has risk to suffer hypertension) and people with hypertension.
A statistical process was made with this sample in which multivariate techniques as Discriminant Analysis and Logistic Regression were used. The results of these techniques and the application of the Fuller’s Triangle Method were used in the system for ranking the hypertension risk factors and for obtain their importance grade (weigh). CHAID technique allowed reduces the comparisons of the cases making more efficient this process. With the application of the analysis of variance (ANOVA) and TwoStep Cluster Analysis the features comparison function for continuous variables was obtained.
With all this information the likeness function was build to compare the new case with the rest of cases of the case base. The adaptation of the solution of the most similar cases was carried out with the application of nearest k-neighbors algorithm.
Finally the system was validated and was checked an effectiveness of 96%.
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http://es.wikipedia.org/wiki/Hipertensi%C3%B3n_arterial. Consultado el 23 de septiembre de 2010.
M. D. P. Caballero, A. D. Herrera, J. A. Guerra, A. V. Vigoa. Hipertensión Arterial. Guía para la prevención, diagnóstico y tratamiento. J. Quesada (editor). 1ª ed. Ed. Ciencias Médicas. La Habana, Cuba. 2008. pp. 9- 22.
http://www.drscope.com/cardiologia/pac/arterial.htm. Consultado el 13 de Septiembre de 2010.
R. D. Feldman, G. Y. Zou, M. K. Vandervoort. “A simplified approach to the treatment of uncomplicated hypertension. A cluster randomized controlled trial”. Hypertension. Vol. 53. 2009. pp. 646-653. DOI: https://doi.org/10.1161/HYPERTENSIONAHA.108.123455
D. L. Clement, M. L. De Buyzere, D. A. De Bacquer. “Prognostic value of ambulatory blood-pressure recordings in patients with treated hypertension”. J Med. Vol. 348. 2003. pp. 2407-2415. DOI: https://doi.org/10.1056/NEJMoa022273
K. Bjorklund, L. Lind, B. Zethelius. “Prognostic significance of 24-h ambulatory blood pressure characteristics for cardiovascular morbidity in a population of elderly men”. Hypertension. Vol. 22. 2004. pp. 1691-1697. DOI: https://doi.org/10.1097/00004872-200409000-00012
http://scielo.sld.cu/scielo.php?pid=S0864-21251996000200007&script=sci_arttext. Consultado el 13 de septiembre de 2010.
J. L. Kolodner. “An Introduction to Case-Based Reasoning”. Artificial Intelligence Review. Vol. 6. 1992. pp. 3-34. DOI: https://doi.org/10.1007/BF00155578
F. Mariiel. “CBR: A categorized bibliography”. The Knowledge Engineering Review. Vol. 9. 1994. pp. 1-36.
A. Aamodt, E. Plaza. “CBR: foundational issues, methodological variations and systems approach”. AI Communications. Vol. 7. 1996. pp. 1-22. DOI: https://doi.org/10.3233/AIC-1994-7104
W. Dubitzky. Knowledge Integration in Case-Based Reasoning: A Concept-Centred Approach. Thesis submitted in application for the degree of Doctor of Philosophy. Faculty of Informatics, University of Ulster, The United Kingdom. 1997. pp. 226-231.
I. G. Martínez, R. E. Bello, Y. C. Bergolla. URSHTA: Sistema de Razonamiento en condiciones de Incertidumbre para el diagnóstico de la HTA. II Simposio Internacional de Hipertensión Arterial. Ed. Feijoo. Villa Clara (Cuba). 2004. pp. 2-4.
S. C. Rodríguez, G. C. Cardoso. Diagnóstico y detección de factores de riesgo de la HTA usando técnicas estadísticas. III Simposio Internacional de Hipertensión Arterial y I Taller sobre Riesgo Vascular. Ed. Feijoo. Villa Clara, Cuba. 2006. pp. 6-8.
A. P. de Armas, O. G. Blanco, H. C. Hernández, E. G. Rodríguez, Y. L. Carvajal, S. C. Rodríguez. Nuevos métodos para el pesquisaje y el diagnóstico precoz de la hipertensión arterial esencial. III Simposio Internacional de Hipertensión Arterial y I Taller sobre Riesgo Vascular. Ed. Feijoo. Villa Clara, Cuba. 2006. pp. 2-4.
P. Armario, R. Hernández del Rey, M. Martín. “Estrés, enfermedad cardiovascular e hipertensión arterial”. Medicina Clínica. Vol. 119. 2002. pp. 23-29. DOI: https://doi.org/10.1016/S0025-7753(02)73301-0
R. S. Vasan, M. G. Larson, E. P. Leip, J. C. Evans, Ch. J. O′Donell, W. B. Kannel, D. Levy. “Impact of HighNormal blood pressure on the risk of cardiovascular disease”. J Med. Vol. 345. 2001. pp. 1291-1297. DOI: https://doi.org/10.1056/NEJMoa003417
M. Benet, A. J. Yanes, L. J. González, J. J. Apolinaire, J. García del Pozo. “Criterios diagnósticos de la prueba del peso sostenido en la detección de pacientes con hipertensión arterial”. Medicina Clínica. Vol. 116. 2001. pp. 645-649. DOI: https://doi.org/10.1016/S0025-7753(01)71936-7
W. Wilke, R. Bergmann. Considering Decision Cost During Learning of Features Weights. Ed. SpringerLink. University of Kaiserslautern, Germany. 1996. pp. 460–472 DOI: https://doi.org/10.1007/BFb0020630
S. Cuadrado, G. Casas. Tensoft: Sistema informativo para el diagnóstico de la HTA sobre bases estadísticas. Tesis presentada en opción al título de Master of Science. Universidad Central de Las Villas. Santa Clara, Cuba. 2006. pp. 26-44.
I. Watson, F. Marir. “Case-Based Reasoning: A review”. The Knowledge Engineering Review. Vol. 9. 1994. pp. 355-381. DOI: https://doi.org/10.1017/S0269888900007104
J. S. Breese, D. Heckerman. Decision-theoretic casebased reasoning. Fifth International Workshop on Artificial Intelligence and Statistics. Fort Lauderdale, Florida. January. 1995. pp. 56-63.
I. Gutiérrez, R. Bello. “A Decision Case-Based System, that reasons in Uncertainty Conditions”. Lecture Notes in Artificial Intelligence (LNAI 2504). Berlín. Ed. Springer Link. 2002. pp. 54-63. DOI: https://doi.org/10.1007/3-540-36079-4_5
L. Ceccaroni. “Introducción a los sistemas basados en el conocimiento”. Inteligencia Artificial. Vol. 12. 2008. pp. 25-45.
I. Watson, F. Marir. Case-Based Reasoning: A Review. University of Auckland. New Zealand. Vol. 3. 2000. pp. 355-381.
M.Tabucanon. Multiple criteria decision making in industry. Ed. Elsevier. Amsterdam. 1988. pp. 233-299.
S. Milton. “Statistical Methods in the Biological and Health Sciences”. Statistics. 3rd ed. Ed. McGraw-Hill. New York. Vol. 1. 1999. pp. 586.
J. Jacqueline, Meulman, W. J. Heiser. Manual de SPSS. Ed. Oxford: Oxford University Press. 2004. pp. 49-90.
S. Glantz. Primer of biostatistics. 5th ed. Ed. McGrawHill. Vol. 1. 2002. pp. 468.
A. Field. Discovering Statistics Using SPSS for Windows. Advanced Techniques for the Beginner. Ed. U.o.S. Daniel B. Wright. Vol. 1. 2003. pp. 496.
A. Aron, E. Aron. Statistics for the Behavioral and Social Sciences. A Brief Course. 2nd ed. Ed Prentice Hall. Vol. 1. 2002. pp. 330.
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