Abstract
This paper presents the application of this new tool of data processing in the study of the problem that arises when a renal transplant is indicated for a paediatric patient. Its aim is the development and validation of a neural network based model which can predict the success of the transplant over the short, medium and long term, using pre-operative characteristics of the patient (recipient) and implant organ (donor). When compared to results of logistic regression, the results of the proposed model showed better performance. Once the model is obtained, it will be converted into a tool for predicting the efficiency of the transplant protocol in order to optimise the donor-recipient pair and maximize the success of the transplant. The first real use of this application will be as a decision aid tool for helping physicians and surgeons when preparing to perform a transplant.
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Magdalena, R., Serrano, A.J., Serrano, A., Muñoz, J., Vila, J., Soria, E. (2004). Design of a Neural Network Model as a Decision Making Aid in Renal Transplant. In: Barreiro, J.M., Martín-Sánchez, F., Maojo, V., Sanz, F. (eds) Biological and Medical Data Analysis. ISBMDA 2004. Lecture Notes in Computer Science, vol 3337. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30547-7_17
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DOI: https://doi.org/10.1007/978-3-540-30547-7_17
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