Random Forest Analysis: A New Approach for Classification of Beta Thalassemia

14 Pages Posted: 19 Mar 2020

See all articles by Massimiliano Sacco

Massimiliano Sacco

Campus of Hematology Franco and Piera Cutino

Mariangela Sciandra

University of Palermo - d/SEAS

Aurelio Maggio

Campus of Hematology Franco and Piera Cutino

Date Written: March 19, 2020

Abstract

In recent years, Thalassemia care providers started classifying patients as transfusion-dependent-Thalassemia (TDT) or non-transfusion-dependent-Thalassemia (NTDT) owing to the established role of transfusion therapy in defining the clinical complication profile, although this classification was also based on expert opinion and is limited by reliance on patients’current transfusion status. Starting from a vast set of variables indicating severity phenotype, through the use of both classification and clustering techniques we want to explore the presence of two (TDT vs NTDT) or more clusters, in order to approaching to a new definition for the classification of Beta-Thalassemia in Thalassemia Syndromes (TS).

Keywords: Random forest, Unsupervised classification, Clustering, Thalassemia

Suggested Citation

Sacco, Massimiliano and Sciandra, Mariangela and Maggio, Aurelio, Random Forest Analysis: A New Approach for Classification of Beta Thalassemia (March 19, 2020). d/SEAS Working Paper Forthcoming, Available at SSRN: https://ssrn.com/abstract=3557120 or http://dx.doi.org/10.2139/ssrn.3557120

Massimiliano Sacco (Contact Author)

Campus of Hematology Franco and Piera Cutino

AOOR Villa Sofia-V. Cervello
Palermo
Italy

Mariangela Sciandra

University of Palermo - d/SEAS

Viale delle Scienze, edificio 13
Palermo, 90124
Italy

Aurelio Maggio

Campus of Hematology Franco and Piera Cutino ( email )

AOOR Villa Sofia-V. Cervello
Palermo
Italy

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