Skip to main content
SpringerLink
Log in
Book cover

World Summit on Knowledge Society

WSKS 2009: Best Practices for the Knowledge Society. Knowledge, Learning, Development and Technology for All pp 522–531Cite as

Towards the Neuropsychological Diagnosis of Alzheimer’s Disease: A Hybrid Model in Decision Making

  • Conference paper

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 49))

Abstract

Dementias are syndromes described by a decline in memory and other neuropsychological changes especially occurring in the elderly and increasing exponentially in function of age. Due to this fact and the therapeutical limitations in the most advanced stage of the disease, diagnosis of Alzheimer’s disease is extremely important and it can provide better life conditions to patients and their families. This work presents a hybrid model, combining Influence Diagrams and the Multicriteria Method, for aiding to discover, from a battery of tests, which are the most attractive questions, in relation to the stages of CDR (Clinical Dementia Rating) in decision making for the diagnosis of Alzheimer’s disease. This disease is the most common dementia. Influence Diagram is implemented using GeNie tool. Next, the judgment matrixes are constructed to obtain cardinal value scales which are implemented through MACBETH Multicriteria Methodology. The modeling and evaluation processes were carried out through a battery of standardized assessments for the evaluation of cases with Alzheimer’s disease developed by Consortium to Establish a Registry for Alzheimer’s disease (CERAD).

This is a preview of subscription content, log in via an institution.

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Bana e Costa, C.A., Corte, J.M.D., Vansnick, J.C.: MACBETH. LSE-OR Working Paper, 56 (2003)

    Google Scholar 

  2. Bana e Costa, C.A., Corte, J.M.D., Vansnick, J.C.: Software M-MACBETH version 1.1. European Working Group “Multiple Criteria Decision Aiding 3(12) (2005a)

    Google Scholar 

  3. Bana e Costa, C.A., Corte, J.M.D., Vansnick, J.C.: On the Mathematical Foundations of MACBETH. In: Figueira, J., Greco, S., Ehrgott, M. (eds.) Multiple Criteria Decision Analysis: State of the Art Surveys Series: International Series in Operations Research & Management Science, vol. 78, XXXVI, pp. 410–442 (2005b)

    Google Scholar 

  4. Bana e Costa, C.A., Ensslin, L., Correa, E.C., Vansnick, J.C.: Decision support systems in action: integrates application in a multicriteria decision aid process. European Journal of Operational Research 133, 315–335 (1999)

    Article  Google Scholar 

  5. Bassett, S.S.: Attention: Neuropsychological Predictor of Competency in Alzheimer’s Disease. Journal of Geriatric Psychiatry and Neurology 12, 200–205 (1999)

    Article  Google Scholar 

  6. Castro, A.K.A., Pinheiro, P.R., Pinheiro, M.C.D.A.: A Multicriteria Model Applied in the Diagnosis of Alzheimer’s Disease. In: Wang, G., Li, T., Grzymala-Busse, J.W., Miao, D., Skowron, A., Yao, Y. (eds.) RSKT 2008. LNCS (LNAI), vol. 5009, pp. 612–619. Springer, Heidelberg (2008a)

    Chapter  Google Scholar 

  7. Castro, A.K.A., Pinheiro, P.R., Pinheiro, M.C.D.A.: A Hybrid Model for Aiding in Decision Making for the Neuropsychological Diagnosis of Alzheimer’s Disease. In: Chan, C.-C., Grzymala-Busse, J.W., Ziarko, W.P. (eds.) RSCTC 2008. LNCS (LNAI), vol. 5306, pp. 495–504. Springer, Heidelberg (2008b)

    Chapter  Google Scholar 

  8. Detwarasiti, A., Shachter, R.D.: Influence Diagrams for Team Decision Analysis. Decision Analysis 2(4), 207–228 (2005)

    Article  Google Scholar 

  9. Evangelou, C., Karacapilidis, N., Khaled, O.A.: Interweaving knowledge management, argumentation and decision making in a collaborative setting: the KAD ontology model. Int. J. of Knowledge and Learning 2005 1(1/2), 130–145 (2005)

    Article  Google Scholar 

  10. Fillenbaum, G.G., van Bellec, G., Morris, J.C., Mohs, R.C., Mirraf, S.S., Davis, P.C., Tariot, P.N., Silvermani, J.M., Clarkj, C.M., Welsh-Bohmer, K.A., Heymanl, A.: Consortium to Establish a Registry for Alzheimer’s Disease (CERAD): The first twenty years. Alzheimer’s & Dementia 4, 96–109 (2008)

    Article  Google Scholar 

  11. Genie. Graphical Network Interface. Decision Systems Laboratory, University of Pittsburgh (2008)

    Google Scholar 

  12. Heyman, A., Peterson, B., Fillenbaum, G., Pieper, C.: The Consortium to Establish a Registry for Alzheimer’s Disease (CERAD). Part XIV: Demographic and clinical predictors of survival in patients with Alzheimer’s disease. Neurology 46(3), 656–660 (1996)

    Google Scholar 

  13. Howard, R.A., Matheson, J.E.: Influence Diagrams. Decision Analysis 2(3), 127–143 (2005)

    Article  Google Scholar 

  14. Hughes, C.P., Berg, L., Danzinger, W.L., Coben, L.A., Martin, R.L.: A New Clinical Scale for the Staging of Dementia. British Journal of Psychiatry 140, 566–572 (1982)

    Article  Google Scholar 

  15. Jorm, A.F., Jacomb, P.A.: The Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE): Socio-Demographic Correlates, Reliability, Validity and Some Norms. Psychol. Med. 19, 1015–1022 (1989)

    Article  Google Scholar 

  16. Kjærulff, U.B., Madsen, A.L.: Bayesian Networks and Influence Diagrams: A Guide to Construction and Analysis. Series: Information Science and Statistics, XVIII, 318 p. Springer, Heidelberg (2007)

    Google Scholar 

  17. Korb, K.B., Nicholson, A.E.: Bayesian Artificial Intelligence. Chapman & Hall/CRC (2003)

    Google Scholar 

  18. Korhonen, P.: Interactive Methods. In: Figueira, J., Greco, S., Ehrgott, M. (eds.) Multiple Criteria Decision Analysis: State of the Art Surveys. Series: International Series in Operations Research & Management Science, vol. 78, XXXVI, pp. 641–665 (2005)

    Google Scholar 

  19. Marilia, M., Carvalho, A.L., Furtado, M.E.S., Pinheiro, P.R.: Co-evolutionary Interaction Design of Digital TV Applications Based on Verbal Decision Analysis of User Experiences. In: WSKS 2008. Communications in Computer and Information Science, vol. 19, pp. 702–711 (2008), doi:0.1007/978-3-540-87783-7

    Google Scholar 

  20. Marilia, M., Carvalho, A.L., Furtado, M.E.S., Pinheiro, P.R.: A co-evolutionary interaction design of digital TVapplications based on verbal decision analysis of user experiences. International Journal of Digital Culture and Electronic Tourism (IJDCET) 1, 312–324 (2009)

    Google Scholar 

  21. Mohr, E., Dastoor, D., Claus, J.J.: Neuropsychological Assessment. In: Gauthier, S. (ed.) Clinical Diagnosis and Management of Alzheimer’s Disease, pp. 93–106. Martin Dunitz, London (1999)

    Google Scholar 

  22. Moms, J.C., Heyman, A., Mohs, R.C., Hughes, J.P., van Belle, G., Fillenbaum, G., Mellits, E.D., Clark, C.: Part I. Clinical and neuropsychological assesment of Alzheimer’s disease The Consortium to Establish a Registry for Alzheimer’s Disease (CERAD). Neurology 39, 1159–1165 (1989)

    Google Scholar 

  23. Morris, J.C., Heyman, A., Mohs, R.C., et al.: The Consortium to Establish a Registry for Alzheimer’s Disease (CERAD): Part 1. Clinical and Neuropsychological Assessment of Alzheimer’s Disease. Neurology 39, 1159–1165 (1989)

    Google Scholar 

  24. Ostrosky-Solis, A.-R.M.: NEUROPSI: A Brief Neuropsychological Test Battery in Spanish with Norms by Age and Educational Level. J. Int. Neuropsychol.Soc. 5, 413–433 (1999)

    Article  Google Scholar 

  25. Petersen, R.C., Smith, G.E., Waring, S.C., et al.: Mild Cognitive Impairment: Clinical Characterization and Outcome. Archives Neurology 56, 303–308 (1999)

    Article  Google Scholar 

  26. Pinheiro, P.R., Castro, A.K.A., Pinheiro, M.C.D.: Multicriteria Model Applied in the Diagnosis of Alzheimer’s Disease: A Bayesian Network. In: Proceedings of the 11th IEEE International Conference on Computational Science and Engineering, São Paulo, vol. 1, pp. 15–22. IEEE Computer Society, Danvers (2008)

    Chapter  Google Scholar 

  27. Porto, C.S., Fichman, H.C., Caramelli, P., Bahia, V.S., Nitrini, R.: Brazilian Version of the Mattis Dementia Rating Scale Diagnosis of Mild Dementia in Alzheimer.s Disease. Arq. Neuropsiquiatr. 61(2-B), 339–345 (2003)

    Google Scholar 

  28. Prince, M.J.: Predicting the Onset of Alzheimer’s Disease Using Bayes’ Therorem. American Journal of Epidemiology 43, 301–308 (1996)

    Google Scholar 

  29. Rosen, W.G., Mohs, R.C., Davis, K.L.: A New Rating Scale for Alzheimer’ s Disease. Am. J. Psychiatry 141, 1356–1364 (1984)

    Google Scholar 

  30. Roth, M., Tym, E., Mountjoy, C.Q., et al.: CAMDEX - A Standardized Instrument for the Diagnosis of Mental Disorder in the Elderly with Special Reference to the Early Detection of Dementia. Br. J. Psychiatry 149, 698–709 (1986)

    Article  Google Scholar 

  31. Welsh, K., Butters, N., Hughes, J., Mohs, R., Heyman, A.: Detection of Abnormal Memory Decline in Mild Cases of Alzheimer’s Disease Using CERAD Neuropsychological Measures. Arch. Neurol. 48, 278–281 (1991)

    Google Scholar 

  32. Welsh, K.A., Butters, N., Mohs, R.C., Beekly, D., Edland, S., Fillenbaum, G., et al.: The Consortium to Establish a Registry for Alzheimer’s Disease (CERAD): part V—a normative study of the neuropsychological battery. Neurology 44, 609–614 (1994)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Graduate Program in Applied Informatics, University of Fortaleza, Av. Washington Soares, 1321 - Bloco J sala 30, CEP: 60811-905, Fortaleza, Ceara, Brazil

    Ana Karoline Araujo de Castro, Placido Rogerio Pinheiro & Mirian Caliope Dantas Pinheiro

Authors
  1. Ana Karoline Araujo de Castro
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Placido Rogerio Pinheiro
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Mirian Caliope Dantas Pinheiro
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Open Research Society, Gerakas Attikis, NGO, Greece

    Miltiadis D. Lytras

  2. University of Ovieto, Spain

    Patricia Ordonez de Pablos

  3. Department of Information Technology, University of Milan, via Bramante, 65 - 26013, Crema (CR), Italy

    Ernesto Damiani

  4. ESSEC Business School, Cergy Pontoise Cedex, France

    David Avison

  5. KMR group at NADA/KTH (Royal Institute of Technology), Lindstedtsv. 5, P.O. Box, 100 44, Stockholm, Sweden

    Ambjörn Naeve

  6. The American College of Greece, Greece

    David G. Horner

Rights and permissions

Reprints and permissions

Copyright information

© 2009 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

de Castro, A.K.A., Pinheiro, P.R., Pinheiro, M.C.D. (2009). Towards the Neuropsychological Diagnosis of Alzheimer’s Disease: A Hybrid Model in Decision Making. In: Lytras, M.D., Ordonez de Pablos, P., Damiani, E., Avison, D., Naeve, A., Horner, D.G. (eds) Best Practices for the Knowledge Society. Knowledge, Learning, Development and Technology for All. WSKS 2009. Communications in Computer and Information Science, vol 49. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04757-2_56

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-04757-2_56

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-04756-5

  • Online ISBN: 978-3-642-04757-2

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation