Skip to main content
Book cover

Multimedia Services in Intelligent Environments pp 39–61Cite as

Smart Recommendation Services in Support of Patient Empowerment and Personalized Medicine

Part of the Smart Innovation, Systems and Technologies book series (SIST,volume 25)

Abstract

Medicine is undergoing a revolution that is transforming the nature of healthcare from reactive to preventive. The changes are catalyzed by a new systems approach to disease which focuses on integrated diagnosis, treatment and prevention of disease in individuals. This will replace our current mode of medicine over the coming years with a personalized predictive treatment. While the goal is clear, the path is fraught with challenges. The p-medicine EU project aspires to create an infrastructure that will facilitate this translation from current medical practice to personalized medicine. This Chapter focus on current research activities related to the design and implementation of an intelligent patient empowerment platform and its services. The focus of our work concerns the nature of the interaction between health institutions and individuals, particularly the communicative relation between physicians and patients, the ways of exchanging information, the nature of the information itself and the information assimilation capabilities of the patients. Our practical focus is the domain of cancer patients, whether in normal treatment or participating in clinical trials. The ultimate objective is to implement a smart environment (recommender system) able to act as a decision support infrastructure to support the communication, interaction and information delivery process form the doctor to the patient. A prerequisite of personalized delivery of information and intelligent guidance of the patient into his/her treatment plans is our ability to develop an appropriate and accurate profile of the user. In the p-medicine project we focus on modeling and profiling the psycho-cognitive capabilities of the patient based on questionnaires and other information features and behaviors extracted from a personal health record of the patient. In this chapter we will provide a systematic review of user profiling techniques and approaches and present our results in developing a psycho-cognitive profile of the user/patient. Subsequently we will describe the details and challenges of implementing the recommendation system and services using a combination of methods to counter-balance the intrinsic weaknesses in various algorithmic approaches. We will review solutions that have combined demographic user classes and content-based filters using implicit behavior and explicit preferences, collaborative filtering and demographic or collaborative filtering and knowledge-based filters. Finally, our approach will be fully described, which uses an adaptive user interface for the presentation of the e-consent, an ontology and a semantic web rule language to formally describe patient choices, and a reasoning engine to handle access and personalized delivery of pertinent disease related information.

Keywords

  • Personalized Medicine
  • User Profile
  • Association Rule Mining
  • Patient Profile
  • Personal Health Record

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

This is a preview of subscription content, access via your institution.

Chapter
USD   29.95
Price excludes VAT (USA)
  • DOI: 10.1007/978-3-319-00375-7_4
  • Chapter length: 23 pages
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
eBook
USD   109.00
Price excludes VAT (USA)
  • ISBN: 978-3-319-00375-7
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
Softcover Book
USD   139.99
Price excludes VAT (USA)
Hardcover Book
USD   169.99
Price excludes VAT (USA)
Learn about institutional subscriptions
Fig. 1
Fig. 2
Fig. 3
Fig. 4

Notes

  1. 1.

    http://www.p-medicine.eu/

  2. 2.

    http://www.cs.waikato.ac.nz/ml/weka/

  3. 3.

    http://www.bioconductor.org/

  4. 4.

    http://biomoby.open-bio.org/

  5. 5.

    http://home.tolven.org/

  6. 6.

    http://healthit.hhs.gov/portal/server.pt/community/healthit_hhs_gov__home/1204

  7. 7.

    http://www.ietf.org/rfc/rfc2251.txt

  8. 8.

    http://www.hl7.org/implement/standards/index.cfm?ref=nav

References

  1. Cawsey, A., Grasso, F., Paris, C.: Adaptive information for consumers of healthcare. In: Peter, B., Alfred, K., Wolfgang, N. (eds.) The Adaptive Web, pp. 465–484. Springer-Verlag (2007)

    Google Scholar 

  2. Luciano, J.S., Andersson, B., Batchelor, C., Bodenreider, O., Clark, T., Denney, C.K., Domarew, C., Gambet, T., Harland, L., Jentzsch, A., Kashyap, V., Kos, P., Kozlovsky, J., Lebo, T., Marshall, S.M., McCusker, J.P., McGuinness, D.L., Ogbuji, C., Pichler, E., Powers, R.L., Prud’hommeaux, E., Samwald, M., Schriml, L., Tonellato, P.J., Whetzel, P.L., Zhao, J., Stephens, S., Dumontier, M.: The translational medicine ontology and knowledge base: Driving personalized medicine by bridging the gap between bench and bedside. J. Biomed. Semant 2(Suppl 2), S1 (2011)

    Google Scholar 

  3. Schiaffino, S., Amandi, A.: Intelligent user profiling artificial intelligence an international perspective. In: Bramer, M. (ed.), vol. 5640, pp. 193–216. Springer Berlin (2009)

    Google Scholar 

  4. Horvitz, E., Breese, J., Heckerman, D., Hovel, D., Rommelse, K.: The lumiere project: Bayesian user modeling for inferring the goals and needs of software users. In: Proceedings of the 14th Conference on Uncertainty in Artificial Intelligence, pp. 256–265 (1998)

    Google Scholar 

  5. Greer, J., Koehn, G.: The peculiarities of plan recognition for intelligent tutoring systems (1995)

    Google Scholar 

  6. Goldberg, L.R.: The structure of phenotypic personality traits. Am. Psychol. 48, 26–34 (1993)

    CrossRef  Google Scholar 

  7. McCrae, R., Costa Jr., P.T: Toward a new generation of personality theories: Theoretical contexts for the five-factor model. In: Wiggins, J.S. (ed.) The five-factor model of personality: Theoretical perspectives, pp. 51–87. Guilford (1996)

    Google Scholar 

  8. Eysenck, H.J.: Personality and prediction: Principles of personality assessment. In: Wiggins J.S. (ed.) Personality and individual differences 11, p. 97 (1990)

    Google Scholar 

  9. Arya, A., Jefferies, L.N., Enns, J.T., DiPaola, S.: Facial actions as visual cues for personality. Comput. Animation Virtual World 17, 371–382 (2006)

    CrossRef  Google Scholar 

  10. Abowd, G.D., Dey, A.K., Brown, P.J., Davies, N., Smith, M., Steggles, P.: Towards a better understanding of context and context-awareness. In: Proceedings of the 1st International Symposium on Handheld and Ubiquitous Computing, pp. 304–307. Springer-Verlag, Karlsruhe, Germany (1999)

    Google Scholar 

  11. Lieberman, H., Fry, C., Weitzman, L.: Exploring the web with reconnaissance agents. Commun. ACM 44, 69–75 (2001)

    CrossRef  Google Scholar 

  12. Godoy, D., Schiaffino, S., Amandi, A.: Interface agents personalizing web-based tasks. Cogn. Syst. Res. 5, 207–222 (2004)

    CrossRef  Google Scholar 

  13. Brusilovsky, P., Sosnovsky, S., Shcherbinina, O.: User modeling in a distributed e-learning architecture. In: Proceedings of the 10th International Conference on User Modeling, pp. 387–391. Springer-Verlag, Edinburgh, UK (2005)

    Google Scholar 

  14. Chen, C.M., Hsieh, Y.L.: Mining learner profile utilizing association rule for common learning misconception diagnosis. In: Proceedings of the 5th IEEE International Conference on Advanced Learning Technologies, pp. 588–592. IEEE Computer Society (2005)

    Google Scholar 

  15. Armentano, M., Amandi, A.: A bayesian networks approach to plan recognition for interface agents. Argentine Symposium on Artificial Intelligence, pp. 1–12 (2006)

    Google Scholar 

  16. Valderas, J.M., Alonso, J., Guyatt, G.H.: Measuring patient-reported outcomes: Moving from clinical trials into clinical practice. Med. J. Aust. 189, 93–94 (2008)

    Google Scholar 

  17. Greenhalgh, J., Meadows, K.: The effectiveness of the use of patient-based measures of health in routine practice in improving the process and outcomes of patient care: A literature review. J Eval. Clin. Pract. 5, 401–416 (1999)

    CrossRef  Google Scholar 

  18. Jensen, F.V., Nielsen, T.D.: Bayesian Networks and Decision Graphs (3 edn). Springer Verlag (2007)

    Google Scholar 

  19. Shah, D., Lakshmanan, L.V.S., Ramamritham, K., Sudarshan, S.: Interestingness and pruning of mined patterns. In: ACM SIGMOD Workshop on Research Issues in Data Mining (1999)

    Google Scholar 

  20. Kolodner, J.L.: Special issue on case-based reasoning: Introduction. Mach. Learn. 10, 195–199 (1993)

    CrossRef  Google Scholar 

  21. Kay, J.: Um: A user modeling toolkit. User Modeling Workshop (1990)

    Google Scholar 

  22. Geissler, J.: Informations to patients debate: As if the internet was still a walled garden (2010)

    Google Scholar 

  23. Ratzan, S., Parker, R.: National library of medicine current bibliographies in medicine: Health literacy. In: Health, N.I.O. (ed.), (2000)

    Google Scholar 

  24. Nielsen-Bohlman, L., Panzer, A.M.: Health Literacy: A Prescription to End Confusion. The National Academies Press, Washington, D.C. (2004)

    Google Scholar 

  25. Neuman, H.B., Charlson, M.E., Temple, L.K.: Is there a role for decision aids in cancer-related decisions? Crit. Rev. Oncol. Hematol. 62, 240–250 (2007)

    CrossRef  Google Scholar 

  26. Barnato, A.E., Llewellyn-Thomas, H.A., Peters, E.M., Siminoff, L., Collins, E.D., Barry, M.J.: Communication and decision making in cancer care: Setting research priorities for decision support/patients’ decision aids. Med. Decis. Mak. 27, 626–634 (2007)

    CrossRef  Google Scholar 

  27. Jacobsen, P.B.: Screening for psychological distress in cancer patients: Challenges and opportunities. J. Clin. Oncol. 25, 4526–4527 (2007)

    CrossRef  Google Scholar 

  28. Yannibelli, V., Godoy, D., Amandi, A.: A genetic algorithm approach to recognise students’ learning styles. Interact. Learn. Environ. 14, 55–78 (2006)

    CrossRef  Google Scholar 

  29. Villaverde, J.E., Godoy, D., Amandi, A.: Learning styles’ recognition in e-learning environments with feed-forward neural networks. J. Comput. Assist. Learn. 22, 197–206 (2006)

    CrossRef  Google Scholar 

  30. Lathia, N., Hailes, S., Capra, L.: kNN CF: A temporal social network. In: Proceedings of the 2008 ACM Conference on Recommender Systems, pp. 227–234. ACM, Lausanne, Switzerland (2008)

    Google Scholar 

  31. Martin-Bautista, M.J., Vila, M.A., Larsen, H.L.: Building adaptive user profiles by a genetic fuzzy classifier with feature selection. In: The 9th IEEE International Conference on Fuzzy Systems, vol. 301, pp. 308–312 (2000)

    Google Scholar 

  32. Gorini, A., Pravettoni, G.: P5-medicine: A plus for a personalized approach to oncology. Nat. Rev. Clin. Oncol. 8, 444 (2011)

    CrossRef  Google Scholar 

  33. Zabora, J., BrintzenhofeSzoc, K., Curbow, B., Hooker, C., Piantadosi, S.: The prevalence of psychological distress by cancer site. Psychooncology 10, 19–28 (2001)

    CrossRef  Google Scholar 

  34. Kennard, B.D., Stewart, S.M., Olvera, R., Bawdon, R.E., hAilin, A.O., Lewis, C.P., Winick, N.J.: Nonadherence in adolescent oncology patients: Preliminary data on psychological risk factors and relationships to outcome. J. Clin. Psychol. Med. Settings 11, 31–39 (2004)

    CrossRef  Google Scholar 

  35. von Essen, L., Larsson, G., Oberg, K., Sjoden, P.O.: ‘Satisfaction with care’: Associations with health-related quality of life and psychosocial function among Swedish patients with endocrine gastrointestinal tumours. Eur. J. Cancer Care. 11, 91–99 (2002)

    CrossRef  Google Scholar 

  36. Arndt, V., Merx, H., Sturmer, T., Stegmaier, C., Ziegler, H., Brenner, H.: Age-specific detriments to quality of life among breast cancer patients one year after diagnosis. Eur. J. Cancer 40, 673–680 (2004)

    CrossRef  Google Scholar 

  37. Brezden, C.B., Phillips, K.A., Abdolell, M., Bunston, T., Tannock, I.F.: Cognitive function in breast cancer patients receiving adjuvant chemotherapy. J. Clin. Oncol. 18, 2695–2701 (2000)

    Google Scholar 

  38. Nolen-Hoeksema, S., Wisco, B.E., Lyubomirsky, S.: Rethinking rumination. Perspect. Psychol. Sci. 3, 400–424 (2008)

    CrossRef  Google Scholar 

  39. Bandura, A.: Self-Efficacy: Toward a unifying theory of behavioral change. Psychol. Rev. 84, 191–215 (1977)

    CrossRef  Google Scholar 

  40. Scholz, U., Dona, B.G., Sud, S., Schwarzer, R.: Is general self-efficacy a universal construct? psychometric findings from 25 countries. Eur. J. Psychol. Assess. 18, 242–251 (2002)

    CrossRef  Google Scholar 

  41. Bowling, A., Ebrahim, S.: Measuring patients’ preferences for treatment and perceptions of risk. Quality in health care: QHC 10(Suppl 1):2–8 (2001)

    Google Scholar 

  42. Ellis, P.M., Butow, P.N., Tattersall, M.H.N.: Informing breast cancer patients about clinical trials: A randomized clinical trial of an educational booklet. Ann. Oncol. 13, 1414–1423 (2002)

    CrossRef  Google Scholar 

  43. Sandhu, R., Coyne, E.J., Feinstein, H.L., Youman, C.E.: Role-based access control models. IEEE Comput. (IEEE Press) 29, 38–47 (1996)

    CrossRef  Google Scholar 

Download references

Acknowledgments

The research leading to these results has received funding from the European Community’s Seventh Framework Programme (FP7/2007-2013) under grant agreement N° 270089.

Author information

Authors and Affiliations

  1. Computational Medicine Laboratory, FORTH-ICS, Heraklio, Crete, Greece

    Haridimos Kondylakis, Lefteris Koumakis, Manolis Tsiknakis, Kostas Marias & Eirini Genitsaridi

  2. Department of Applied Informatics and Multimedia, Technological Educational Institute, Heraklion, Crete, Greece

    Manolis Tsiknakis

  3. Centro Interdipartimentale di Ricerca e Intervento sui Processi Decisionali (IRIDe), Università degli Studi di Milano, Milan, Italy

    Gabriella Pravettoni & Alessandra Gorini

  4. Department of Decision Sciences, Milan and eCancer—Cancer Intelligence Limited, Bocconi University, Milan, Italy

    Ketti Mazzocco

Authors
  1. Haridimos Kondylakis
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Lefteris Koumakis
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Manolis Tsiknakis
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Kostas Marias
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Eirini Genitsaridi
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Gabriella Pravettoni
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Alessandra Gorini
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Ketti Mazzocco
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Manolis Tsiknakis .

Editor information

Editors and Affiliations

  1. , Department of Informatics, University of Piraeus, Karaoli&Dimitriou St. 80, Piraeus, 18534, Greece

    George A. Tsihrintzis

  2. , Department of Informatics, University of Piraeus, Karaoli&Dimitriou St. 80, Piraeus, 18534, Greece

    Maria Virvou

  3. University of South Australia, Mawson Lakes, Adelaide, 5095, South Australia, Australia

    Lakhmi C. Jain

Appendix

Appendix

Table 1.

Table 1 List of relevant resources
Full size table

Rights and permissions

Reprints and Permissions

Copyright information

© 2013 Springer International Publishing Switzerland

About this chapter

Cite this chapter

Kondylakis, H. et al. (2013). Smart Recommendation Services in Support of Patient Empowerment and Personalized Medicine. In: Tsihrintzis, G., Virvou, M., Jain, L. (eds) Multimedia Services in Intelligent Environments. Smart Innovation, Systems and Technologies, vol 25. Springer, Heidelberg. https://doi.org/10.1007/978-3-319-00375-7_4

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-00375-7_4

  • Published:

  • Publisher Name: Springer, Heidelberg

  • Print ISBN: 978-3-319-00374-0

  • Online ISBN: 978-3-319-00375-7

  • eBook Packages: EngineeringEngineering (R0)