Case-based Planning of Treatment of Infants with Respiratory Failure

Issue title: Concurrency Specification and Programming (CS&P)

Article type: Research Article

Authors: Góra, Grzegorz | Kruczek, Piotr | Skowron, Andrzej | Bazan, Jan G. | Bazan-Socha, Stanisława | Pietrzyk, Jacek J.

Affiliations: Institute of Mathematics, Warsaw University, Banacha 2, 02-097 Warszawa, Poland. ggora@mimuw.edu.pl | Department of Pediatrics, Collegium Medicum, Jagiellonian University, Wielicka 265, 30-663 Kraków, Poland. kruczekpiotr@poczta.onet.pl | Institute of Mathematics, Warsaw University, Banacha 2, 02-097 Warszawa, Poland. skowron@mimuw.edu.pl | Institute of Mathematics, University of Rzeszów Rejtana 16A, 35-959 Rzeszów, Poland. bazan@univ.rzeszow.pl | Department of Internal Medicine Collegium Medicum, Jagiellonian University, Skawińska 8, 31-066 Kraków, Poland. mmsocha@cyf-kr.edu.pl | Department of Pediatrics, Collegium Medicum, Jagiellonian University, Wielicka 265, 30-663 Kraków, Poland. mipietrz@cyf-kr.edu.pl

Note: [] Address for correspondence: Institute of Mathematics, University of Rzeszów, Rejtana 16A, 35-959 Rzeszów, Poland

Abstract: We discuss medical treatment planning in the context of case-based planning, where plans (of treatment) are treated as complex decisions. A plan for a particular case is constructed from known plans for similar training examples. In order to evaluate and improve the prediction quality of complex decisions, we use a method for approximation of similarity measure between plans. The method makes it possible to transform the acquired domain knowledge about similarities of plans, expressed by medical experts in natural language, to a low level language understandable by the system. To accomplish this task, we developed a method for approximation of the ontology of concepts expressed by medical experts. We present two applications of the ontology approximation, namely, for approximation of similarity between patient histories and for approximation of compatibility of patient histories with planned therapies. Next, we use these concept approximations to define two measures on which are based two methods for (plan) therapy prediction. The article includes results of experiments with these methods performed on medical data obtained from Neonatal Intensive Care Unit, First Department of Pediatrics, Polish-American Institute of Pediatrics, Collegium Medicum, Jagiellonian University, Krak?ow, Poland. The experiments are pertained to the identification of infants' death risk caused by respiratory failure.

Keywords: automated planning, ontology of concepts, respiratory failure, rough sets, ontology approximation, similarity relation approximation

Journal: Fundamenta Informaticae, vol. 85, no. 1-4, pp. 155-172, 2008