Machine Learning and Personalized Modeling for Diagnosis of Acute GvHD: an Integrated Approach

Authors:
Maurizio Fiasché;Maria Cuzzola;Roberta Fedele;Pasquale Iacopino;Francesco C. Morabito
Affiliations:
DIMET, University “Mediterranea” of Reggio Calabria, Italy and Transplant Regional Center of Stem Cells and Cellular Therapy, “A. Neri”, Reggio Calabria, Italy;Transplant Regional Center of Stem Cells and Cellular Therapy, “A. Neri”, Reggio Calabria, Italy;Transplant Regional Center of Stem Cells and Cellular Therapy, “A. Neri”, Reggio Calabria, Italy;Transplant Regional Center of Stem Cells and Cellular Therapy, “A. Neri”, Reggio Calabria, Italy;DIMET, University “Mediterranea” of Reggio Calabria, Italy
Venue:
Proceedings of the 2011 conference on Neural Nets WIRN10: Proceedings of the 20th Italian Workshop on Neural Nets
Year:
2011

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Abstract

In this paper a novel gene selection method based on personalized modeling is presented and is compared with classical machine learning techniques to identify diagnostic gene targets and to use them for a successful diagnosis of a medical problem-acute graft-versus-host disease (aGVHD). An analysis using the integrated approach of new data with the existing models is evaluated. The aGVHD is the major complication after allogeneic haematopoietic stem cell transplantation (HSCT) in which functional immune cells of donor, recognize the recipient as “foreign” and mount an immunologic attack. Identifying a compact set of genes from gene expression data is a critical step in bioinformatics research. Personalized modeling is a recently introduced technique for constructing clinical decision support systems. In this work we have provided a comparative study using the proposed Personalized Modeling based Gene Selection method (PMGS) on the GvHD Macroarray dataset collected. This is the first study which utilises both computational and biological evidence for the involvement of a limited number of genes for the diagnosis of aGVHD and the use of a personalized modeling for the analysis of this disease. Directions for further studies are also outlined.