Abstract
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 %.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Watt, S., Sword, W., Krueger, P.: Longer postpartum hospitalization options—who stays, who leaves, what changes? BMC Pregnancy Childbirth 5, 1–10 (2005)
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)
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)
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)
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)
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)
American Academy of Pediatrics: Committee on Fetus and Newborn: hospital stay for healthy term newborns. Pediatrics 113, 1434–1436 (2004)
American Academy of Pediatrics: Committee on Fetus and Newborn: hospital stay for healthy term newborns. Pediatrics 125, 405–409 (2010)
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)
Aamodt, A., Plaza, E.: Case-based reasoning: Foundational issues, methodological variations, and system approaches. AI Commun. 7, 39–59 (1994)
Richter, M.M., Weber, R.O.: Case-Based Reasoning: A Textbook. Springer, Berlin (2013)
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)
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)
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)
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)
Tsinakos, A.: Asynchronous distance education: teaching using case based reasoning. Turk. Online J Distance Educ. 4, 1–8 (2003)
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)
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)
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)
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)
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)
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)
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)
Almeida, A.: The management systems of archival information on Portuguese public hospitals. Master’s thesis, University of Lisbon (2011)
Cardoso, M.: Auditing an hospital information system—SAM. Master’s thesis, Polytechnic Institute of Bragança (2010)
O’Neil, P., O’Neil, B., Chen, X.: Star schema Benchmark. Revision 3, June 5, 2009. http://www.cs.umb.edu/~poneil/StarSchemaB.pdf
Neves, J., Vicente, H.: Quantum approach to Case-Based Reasoning (in preparation)
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)
Dice, L.R.: Measures of the amount of ecologic association between species. Ecology 26, 297–302 (1945)
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.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing Switzerland
About this paper
Cite this paper
Coimbra, A. et al. (2016). Prediction of Length of Hospital Stay in Preterm Infants a Case-Based Reasoning View. In: Czarnowski, I., Caballero, A., Howlett, R., Jain, L. (eds) Intelligent Decision Technologies 2016. IDT 2016. Smart Innovation, Systems and Technologies, vol 56. Springer, Cham. https://doi.org/10.1007/978-3-319-39630-9_10
Download citation
DOI: https://doi.org/10.1007/978-3-319-39630-9_10
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-39629-3
Online ISBN: 978-3-319-39630-9
eBook Packages: EngineeringEngineering (R0)