Prediction of Length of Hospital Stay in Preterm Infants a Case-Based Reasoning View

  • Ana Coimbra
  • Henrique Vicente
  • António Abelha
  • M. Filipe Santos
  • José Machado
  • João Neves
  • José NevesEmail author
Conference paper
Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 56)


The length of stay of preterm infants in a neonatology service has become an issue of a growing concern, namely considering, on the one hand, the mothers and infants health conditions and, on the other hand, the scarce healthcare facilities own resources. Thus, a pro-active strategy for problem solving has to be put in place, either to improve the quality-of-service provided or to reduce the inherent financial costs. Therefore, this work will focus on the development of a diagnosis decision support system in terms of a formal agenda built on a Logic Programming approach to knowledge representation and reasoning, complemented with a case-based problem solving methodology to computing, that caters for the handling of incomplete, unknown, or even contradictory information. The proposed model has been quite accurate in predicting the length of stay (overall accuracy of 84.9 %) and by reducing the computational time with values around 21.3 %.


Preterm infants Length of stay Neonatology Knowledge representation and reasoning Logic programming Case-based reasoning 



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.


  1. 1.
    Watt, S., Sword, W., Krueger, P.: Longer postpartum hospitalization options—who stays, who leaves, what changes? BMC Pregnancy Childbirth 5, 1–10 (2005)CrossRefGoogle Scholar
  2. 2.
    Hintz, S., Bann, C., Ambalavanan, N., Cotten, C., Das, A., Higgins, R.: Predicting time to hospital discharge for extremely preterm infants. Pediatrics 125, e146–e154 (2010)CrossRefGoogle Scholar
  3. 3.
    Adebanji, A., Adeyemi, S., Gyamfi, M.: Empirical analysis of factors associated with neonatal length of stay in Sunyani, Ghana. J. Public Health Epidemiol. 7, 59–64 (2015)CrossRefGoogle Scholar
  4. 4.
    Goyal, N., Zubizarreta, J., Small, D., Lorch, S.: Length of stay and readmission among late pre term infants: an instrumental variable approach. Hosp. Pediatr. 3, 7–15 (2013)CrossRefGoogle Scholar
  5. 5.
    Gupta, P., Malhotra, S., Singh, D., Dua, T.: Length of postnatal stay in healthy newborns and re-hospitalization following their early discharge. Indian J. Pediatr. 73, 897–900 (2006)CrossRefGoogle Scholar
  6. 6.
    Farhat, R., Rajab, M.: Length of postnatal hospital stay in healthy newborns and re-hospitalization following early discharge. North Am. J. Med. Sci. 3, 146–151 (2011)CrossRefGoogle Scholar
  7. 7.
    American Academy of Pediatrics: Committee on Fetus and Newborn: hospital stay for healthy term newborns. Pediatrics 113, 1434–1436 (2004)CrossRefGoogle Scholar
  8. 8.
    American Academy of Pediatrics: Committee on Fetus and Newborn: hospital stay for healthy term newborns. Pediatrics 125, 405–409 (2010)CrossRefGoogle Scholar
  9. 9.
    Niknajad, A., Ghojazadeh, M., Sattarzadeh, N., Hashemi, F., Shahgholi, F.: Factors affecting the neonatal intensive care unit stay duration in very low birth weight premature infants. J. Caring Sci. 1, 85–92 (2012)Google Scholar
  10. 10.
    Aamodt, A., Plaza, E.: Case-based reasoning: Foundational issues, methodological variations, and system approaches. AI Commun. 7, 39–59 (1994)Google Scholar
  11. 11.
    Richter, M.M., Weber, R.O.: Case-Based Reasoning: A Textbook. Springer, Berlin (2013)CrossRefGoogle Scholar
  12. 12.
    Carneiro, D., Novais, P., Andrade, F., Zeleznikow, J., Neves, J.: Using case based reasoning to support alternative dispute resolution. In: Carvalho, A.F., Rodríguez-González, S., Paz-Santana, J.F., Corchado-Rodríguez, J.M. (eds.) Distributed Computing and Artificial Intelligence, Advances in Intelligent and Soft Computing, vol. 79, pp. 123–130. Springer, Berlin (2010)CrossRefGoogle Scholar
  13. 13.
    Carneiro, D., Novais, P., Andrade, F., Zeleznikow, J., Neves, J.: Using case-based reasoning and principled negotiation to provide decision support for dispute resolution. Knowl. Inf. Syst. 36, 789–826 (2013)CrossRefGoogle Scholar
  14. 14.
    Guessoum, S., Laskri, M.T., Lieber, J.: Respidiag: a case-based reasoning system for the diagnosis of chronic obstructive pulmonary disease. Expert Syst. Appl. 41, 267–273 (2014)CrossRefGoogle Scholar
  15. 15.
    Ping, X.-O., Tseng, Y.-J., Lin, Y.-P., Chiu H.-J., Feipei Lai, F., Liang J.-D., Huang, G.-T., Yang, P.-M.: A multiple measurements case-based reasoning method for predicting recurrent status of liver cancer patients. Comput. Ind. 69, 12–21 (2015)Google Scholar
  16. 16.
    Tsinakos, A.: Asynchronous distance education: teaching using case based reasoning. Turk. Online J Distance Educ. 4, 1–8 (2003)Google Scholar
  17. 17.
    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
  18. 18.
    Pereira, L., Anh, H.: Evolution prospection. In: Nakamatsu, K. (ed.) New Advances in Intelligent Decision Technologies—Results of the First KES International Symposium IDT 2009, Studies in Computational Intelligence, vol. 199, pp. 51–64. Springer, Berlin (2009)Google Scholar
  19. 19.
    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
  20. 20.
    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
  21. 21.
    Machado, J., Abelha, A., Novais, P., 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
  22. 22.
    Lucas, P.: Quality checking of medical guidelines through logical abduction. In: Coenen, F., Preece, A., Mackintosh, A. (eds.) Proceedings of AI-2003 (Research and Developments in Intelligent Systems XX), pp. 309–321. Springer, London (2003)Google Scholar
  23. 23.
    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
  24. 24.
    Almeida, A.: The management systems of archival information on Portuguese public hospitals. Master’s thesis, University of Lisbon (2011)Google Scholar
  25. 25.
    Cardoso, M.: Auditing an hospital information system—SAM. Master’s thesis, Polytechnic Institute of Bragança (2010)Google Scholar
  26. 26.
    O’Neil, P., O’Neil, B., Chen, X.: Star schema Benchmark. Revision 3, June 5, 2009.
  27. 27.
    Neves, J., Vicente, H.: Quantum approach to Case-Based Reasoning (in preparation)Google Scholar
  28. 28.
    MacQueen J.B.: Some methods for classification and analysis of multivariate observations. In: Proceedings of the 5th Berkeley Symposium on Mathematical Statistics and Probability, vol. 1, pp. 281–297. University of California Press (1967)Google Scholar
  29. 29.
    Dice, L.R.: Measures of the amount of ecologic association between species. Ecology 26, 297–302 (1945)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Ana Coimbra
    • 1
  • Henrique Vicente
    • 2
    • 3
  • António Abelha
    • 3
  • M. Filipe Santos
    • 3
  • José Machado
    • 3
  • João Neves
    • 4
  • José Neves
    • 3
    Email author
  1. 1.Departamento de InformáticaUniversidade do MinhoBragaPortugal
  2. 2.Departamento de QuímicaEscola de Ciências e Tecnologia Universidade de ÉvoraÉvoraPortugal
  3. 3.Centro AlgoritmiUniversidade do MinhoBragaPortugal
  4. 4.Drs. Nicolas & AspDubaiUnited Arab Emirates

Personalised recommendations