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Waiting Time Screening in Healthcare

  • José NevesEmail author
  • Henrique Vicente
  • Marisa Esteves
  • Filipa Ferraz
  • António Abelha
  • José Machado
  • Joana Machado
  • João Neves
Conference paper
Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST, volume 248)

Abstract

In Medical Imaging (MI), various technologies can be used to monitor the human body for diagnosing, monitoring or treating disease. Each type of technology provides different information about the body area that is being investigated or treated for a possible illness, injury or effectiveness of a medical treatment. Routine screening has identified malfunction detection in many otherwise asymptomatic patient images such as computed tomography or magnetic resonance. Studies have shown that, compared to patients whose disease was symptomatic (i.e., self-recognizing), screen-detected diseases may have more favorable clinicopathological features, leading to better prognosis and better outcome. This paper aims to assess the issue of health care wait screening. It deviates from a decision support system that evaluates the waiting times in diagnostic MI based on operational data from various information systems. Last but not least, one’s assumptions may have an important impact in determining the usefulness of routine laboratory testing at admission.

Keywords

Waiting time screening Logic programming Case-based reasoning 

Notes

Acknowledgments

This work has been supported by COMPETE: POCI-01-0145-FEDER-007043 and FCT – Fundação para a Ciência e Tecnologia within the Project Scope: UID/CEC/00319/2013.

References

  1. 1.
    Nuti, S., Vainieri, M.: Managing waiting times in diagnostic medical imaging. BMJ Open 2, e001255 (2012)CrossRefGoogle Scholar
  2. 2.
    McEnery, K.W.: Radiology information systems and electronic medical records. In: IT Reference Guide for the Practicing Radiologist, pp. 1–14. American College of Radiology, USA (2013)Google Scholar
  3. 3.
    Fotiadou, A.: Choosing and visualizing waiting time indicators in diagnostic medical imaging department for different purposes and audiences. Master’s thesis in Health Informatics, Karolinska Institutet, Sweden (2013)Google Scholar
  4. 4.
    Aamodt, A., Plaza, E.: Case-based reasoning: foundational issues, methodological variations, and system approaches. AI Commun. 7, 39–59 (1994)Google Scholar
  5. 5.
    Richter, M.M., Weber, R.O.: Case-Based Reasoning: A Textbook. Springer, Berlin (2013)CrossRefGoogle Scholar
  6. 6.
    Balke, T., Novais, P., Andrade, F., Eymann, T.: From real-world regulations to concrete norms for software agents – a case-based reasoning approach. In: Poblet, M., Schild, U., Zeleznikow, J. (eds.) Proceedings of the Workshop on Legal and Negotiation Decision Support Systems (LDSS 2009), pp. 13–28. Huygens Editorial, Barcelona (2009)Google Scholar
  7. 7.
    Neves, J.: A logic interpreter to handle time and negation in logic databases. In: Muller, R., Pottmyer, J. (eds.) Proceedings of the 1984 Annual Conference of the ACM on the 5th Generation Challenge, pp. 50–54. Association for Computing Machinery, New York (1984)Google Scholar
  8. 8.
    Neves, J., Machado, J., Analide, C., Abelha, A., Brito, L.: The halt condition in genetic programming. In: Neves, J., Santos, M.F., Machado, J. (eds.) Progress in Artificial Intelligence. LNAI, vol. 4874, pp. 160–169. Springer, Berlin (2007)CrossRefGoogle Scholar
  9. 9.
    Kakas, A., Kowalski, R., Toni, F.: The role of abduction in logic programming. In: Gabbay, D., Hogger, C., Robinson, I. (eds.) Handbook of Logic in Artificial Intelligence and Logic Programming, vol. 5, pp. 235–324. Oxford University Press, Oxford (1998)Google Scholar
  10. 10.
    Pereira, L., Anh, H.: Evolution prospection. In: Nakamatsu, K. (ed.) New Advances in Intelligent Decision Technologies, Studies in Computational Intelligence, vol. 199, pp. 51–64. Springer, Berlin (2009)Google Scholar
  11. 11.
    Machado, J., Abelha, A., Novais, P., Neves, J., Neves, J.: Quality of service in healthcare units. In Bertelle, C., Ayesh, A. (eds.) Proceedings of the ESM 2008, pp. 291–298. Eurosis – ETI Publication, Ghent (2008)Google Scholar
  12. 12.
    Silva, A., Vicente, H., Abelha, A., Santos, M.F., Machado, J., Neves, J., Neves, J.: Length of stay in intensive care units – a case base evaluation. In: Fujita, H., Papadopoulos, G.A. (eds.) New Trends in Software Methodologies, Tools and Techniques, Frontiers in Artificial Intelligence and Applications, vol. 286, pp. 191–202. IOS Press, Amsterdam (2016)Google Scholar
  13. 13.
    Fernandes, F., Vicente, H., Abelha, A., Machado, J., Novais, P., Neves, J.: Artificial neural networks in diabetes control. In: Proceedings of the 2015 Science and Information Conference (SAI 2015), pp. 362–370, IEEE Edition (2015)Google Scholar
  14. 14.
    Turner, M., Fauconnier, G.: Conceptual integration and formal expression. J. Metaphor Symbolic Act. 10, 183–204 (1995)CrossRefGoogle Scholar
  15. 15.
    Vilhena, J., Vicente, H., Martins, M.R., Grañeda, J., Caldeira, F., Gusmão, R., Neves, J., Neves, J.: A case-based reasoning view of thrombophilia risk. J. Biomed. Inf. 62, 265–275 (2016)CrossRefGoogle Scholar
  16. 16.
    Haykin, S.: Neural Networks and Learning Machines. Pearson Education, New Jersey (2009)Google Scholar
  17. 17.
    Figueiredo, M., Esteves, L., Neves, J., Vicente, H.: A data mining approach to study the impact of the methodology followed in chemistry lab classes on the weight attributed by the students to the lab work on learning and motivation. Chem. Educ. Res. Pract. 17, 156–171 (2016)CrossRefGoogle Scholar
  18. 18.
    Florkowski, C.: Sensitivity, specificity, receiver-operating characteristic (ROC) curves and likelihood ratios: communicating the performance of diagnostic tests. Clin. Biochem. Rev. 29(Suppl 1), S83–S87 (2008)Google Scholar
  19. 19.
    Hajian-Tilaki, K.: Receiver operating characteristic (ROC) curve analysis for medical diagnostic test evaluation. Caspian J. Intern. Med. 4, 627–635 (2013)Google Scholar

Copyright information

© ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2018

Authors and Affiliations

  1. 1.Centro AlgoritmiUniversidade do MinhoBragaPortugal
  2. 2.Departamento de Química, Escola de Ciências e Tecnologia, Centro de Química de ÉvoraUniversidade de ÉvoraÉvoraPortugal
  3. 3.Departamento de InformáticaUniversidade do MinhoBragaPortugal
  4. 4.Farmácia de LamaçãesBragaPortugal
  5. 5.Mediclinic Arabian RanchesDubaiUnited Arab Emirates

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