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Case-based Planning of Treatment of Infants with Respiratory Failure

Góra G., Bazan J.G., Kruczek P., Bazan-Socha S., Skowron A., Pietrzyk J.J.

Fundamenta Informaticae

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2008

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Vol. 85, nr 1-4

155-172

EN

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, Kraków, Poland. The experiments are pertained to the identification of infants' death risk caused by respiratory failure.

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Rough Set Approach to Behavioral Pattern Identification

Bazan J.G., Bazan-Socha S., Pietrzyk J.J., Kruczek P., Skowron A.

Fundamenta Informaticae

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2007

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Vol. 75, nr 1-4

27-47

EN

The problem considered is how to model perception and identify behavioral patterns of objects changing over time in complex dynamical systems. An approach to solving this problem has been found in the context of rough set theory and methods. Rough set theory introduced by Zdzisaw Pawlak during the early 1980s provides the foundation for the construction of classifiers, relative to what are known as temporal pattern tables. Temporal patterns can be treated as features that make it possible to approximate complex concepts. This article introduces some rough set tools for perception modeling that are developed for a system for modeling networks of classifiers. Such networks make it possible to identify behavioral patterns of objects changing over time. They are constructed using an ontology of concepts delivered by experts that engage in approximate reasoning about concepts embedded in such an ontology. We also present a method that we call a method for on-line elimination of non-relevant parts (ENP). This method was developed for on-line elimination of complex object parts that are irrelevant for identifying a given behavioral pattern. The article includes results of experiments that have been performed on data from a vehicular traffic simulator and on medical data obtained from Neonatal Intensive Care Unit in the Department of Pediatrics, Collegium Medicum, Jagiellonian University. The contribution of this article is the introduction of a network of classifiers that make it possible to identify the behavioral patterns of objects that change over time.

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Independent lung ventilation as a protective strategy in unilateral lung disease in children

Luchetti M., Marraro G. A., Galassini E. M.

Biocybernetics and Biomedical Engineering

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2003

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Vol. 23, no. 2

77-87

EN

Independent Lung Ventilation (ILV) may be viewed as a lung protective ventilation strategy, since it avoids the overinflation of the healthy lung and allows adequate ventilation of the diseased lung. The aim of this paper is to provide a review of ILV as a protective strategy for the treatment of pediatric respiratory failure due to unilateral lung disease. An analysis of the literature regarding ventilator-associated lung injury, pathophysiology of unilateral lung disease and the efficacy of independent lung ventilation in the pediatric population was carried out. After an overview of unilateral lung disease and initial experience with ILV, the following topical areas are addressed: technique of selective bronchial intubation, mechanical ventilation and ventilator setting, and speculations about the future. Unilateral lung diseases can be treated successfully using SILV. In addition, SILV allows to selectively instilling into the lung medications such as surfactant. Despite its attractive characteristics, ILV has some drawbacks that still limit its use. Investigation in under way trying to simplify the technique and make it more accessible.

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Haemodynamic variations during independent lung ventilation in paediatrics

Marraro G. A., Luchetti M., Galassini E. M.

Biocybernetics and Biomedical Engineering

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2003

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Vol. 23, no. 2

67-76

EN

Independent lung ventilation (ILV) has been suggested in order to reduce volutrauma and barotrauma in the treatment of lung pathology with unilateral prevalence. The application of different PEEP levels to each lung can allow an increase in gas exange and reduce haemodynamic variations connected with high transpulmonary pressure. Application of synchronized ILV with ZEEP or 5 cm H2O PEEP did not in itself cause haemodynamic changes any different from those that occur with intermittent positive pressure ventilation (IPPV) and continuous positive pressure ventilation (CPPV) with 5 cm H2O of positive end-espiratory pressure (PEEP). Maintaining 5 cm H2O of PEEP in the less affected lung and increasing progressively PEEP from 5 to 15 cm H2O in the more pathologic lung, central venous pressure (CVP), cardiac rate and mean arterial pressure (MAP) remained stable. The application of progressive PEEP levels in the less damaged lung while maintaining a stable value in the more damaged lung showed an increase in CVP and cardiac rate and reduction in MAP: Applying synchronised ILV (sILV) an improvement in PaO2 was noted compared to volume controlled ventilation with 10 cm H2O of PEEP. The improvement in PaO2 appears more evident when the "best" PEEP for each lung has been applied.