Journal of Medical Systems

, 39:114 | Cite as

A Clinical Support System Based on Quality of Life Estimation

  • Brígida Mónica FariaEmail author
  • Joaquim Gonçalves
  • Luis Paulo Reis
  • Álvaro Rocha
Patient Facing Systems
Part of the following topical collections:
  1. Health Information Systems & Technologies


Quality of life is a concept influenced by social, economic, psychological, spiritual or medical state factors. More specifically, the perceived quality of an individual’s daily life is an assessment of their well-being or lack of it. In this context, information technologies may help on the management of services for healthcare of chronic patients such as estimating the patient quality of life and helping the medical staff to take appropriate measures to increase each patient quality of life. This paper describes a Quality of Life estimation system developed using information technologies and the application of data mining algorithms to access the information of clinical data of patients with cancer from Otorhinolaryngology and Head and Neck services of an oncology institution. The system was evaluated with a sample composed of 3013 patients. The results achieved show that there are variables that may be significant predictors for the Quality of Life of the patient: years of smoking (p value 0.049) and size of the tumor (p value < 0.001). In order to assign the variables to the classification of the quality of life the best accuracy was obtained by applying the John Platt’s sequential minimal optimization algorithm for training a support vector classifier. In conclusion data mining techniques allow having access to patients additional information helping the physicians to be able to know the quality of life and produce a well-informed clinical decision.


Quality of life Cancer Information technologies Clinical support system Data mining 



This work was funded by QoLis - Quality of Life Platform Project, N°2013/34034 QREN SI I&DT, (NUP, NORTE-07-0202-FEDER-034Ú34). The authors also acknowledge: LIACC (PEst-OE/EEI/UI0027/2014).


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Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  • Brígida Mónica Faria
    • 1
    • 2
    Email author
  • Joaquim Gonçalves
    • 1
    • 3
  • Luis Paulo Reis
    • 1
    • 4
  • Álvaro Rocha
    • 1
    • 5
  1. 1.LIACC – Lab. Inteligência Artificial e Ciência de ComputadoresPortoPortugal
  2. 2.ESTSP/IPP – Esc. Sup. Tecnologia da Saúde do Porto/Instituto Politécnico do PortoVila Nova de GaiaPortugal
  3. 3.EST/IPCA – Esc. Superior de Tecnologia/Instituto Politécnico do Cávado e do AveVila FrescainhaPortugal
  4. 4.Departamento de Sistemas de InformaçãoEEUM – Escola de Engenharia da Universidade do MinhoGuimarãesPortugal
  5. 5.Departamento de Engenharia InformáticaUniversidade de CoimbraCoimbraPortugal

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