Computer Techniques Applied to Transplant Database: Review of Articles Published in the 2007-2008 Biennium - Hummel, Anderson Diniz; Maciel, Rafael Fabio; Falcão, Alex Esteves Jaccoud; Teixeira, Fabio; Cohrs, Frederico Molina; Mancini, Felipe; Costa, Thiago Martini da; Sousa, Fernando Sequeira; Pisa, Ivan Torres (Brazilian Journal of Transplantation, 2009)
For centuries, the human kind has been worrying about replacing defective organs by healthy ones, but only a few decades ago advancements in organ transplantation has made that dream come true. In order to improve the comprehension process and to detect patients whom will have better survival chances, different techniques to assess the organ transplantation database have been used, thus directly or indirectly contributing to discover the not yet mapped knowledge. Purpose: The purpose of this paper is to present from the specialized literature which computational techniques are being used to assess the organ transplantation databases. Methods: it was conducted a review in the literature using the PubMed and ISI databases in abstracts published in the 2007-2008 biennium. Results: After reviewing al abstracts, we selected 89 abstracts, and upon considering the inclusion and exclusion criteria, we selected 5 articles. These have shown that artificial neural networksand logistic regression obtain good results when applied to organs transplantation databases. These articles have demonstrated encouraging results in their respective study databases. Few studies have actually been applied in the clinical practice. Conclusion: When considering the results, the artificial intelligence application techniques attained better results than the normally used techniques to predict based on the transplantation database, and there is potential to the development of clinical decision support system for organ transplantation.