Abstract
This paper presents a hybrid evolutionary algorithm to identify risk factors associated with transfusion related acute lung injury (TRALI). This medical condition occurs mainly in intensive care units and operating rooms, and the main strategy for its treatment is prevention. The proposed algorithm works with information from the model known as “two hits”, in which the first hit is the original disease and the second corresponds to the blood transfusion. This algorithm is based on a genetic algorithm hybridized with testor analysis. This research used information from 87 patients treated at the Centenary Hospital Miguel Hidalgo in the city of Aguascalientes, Mexico. As a result of the algorithm’s application, it was found that most variables are related to the first hit, while only some of them belong to the second one. The analysis also revealed that some variables physicians believed significant a priori, were not very important; among other discoveries.
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Torres, M.D., Torres, A., Cuellar, F., de la Luz Torres, M., de León, E.P., Pinales, F. (2013). Identification of Risk Factors for TRALI Using a Hybrid Algorithm. In: Batyrshin, I., González Mendoza, M. (eds) Advances in Artificial Intelligence. MICAI 2012. Lecture Notes in Computer Science(), vol 7629. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37807-2_37
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DOI: https://doi.org/10.1007/978-3-642-37807-2_37
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