Prediction of a patient´s response to hydroxyurea treatment using artificial neural networks

Author

Valafar, Homayoun ; Valafar, Faramarz

Author_Institution

Georgia Univ., Athens, GA, USA

Volume

1

fYear

1999

fDate

1999

Abstract

The study described in this paper was undertaken to develop the ability to predict the response of sickle-cell patients to hydroxyurea (HU) therapy. We monitored and analyzed the effect of HU on the value of Fetal Hemoglobin (HbF) of 83 patients in order to develop a predictive model for the effect of HU on HbF. Correlation analysis failed to establish a statistically significant relationship between any of the 23 parameters collected from each patient and the magnitude of the HbF response. Linear regression analysis also failed to predict a patient´s response to HU. On the other hand, artificial neural network (ANN) pattern recognition analysis of the 23 parameters predicts, with 86.6% accuracy, those patients that respond positively to HU and those that do not

Keywords

diseases; medical computing; neural nets; patient treatment; artificial neural network; correlation analysis; fetal hemoglobin; hydroxyurea therapy; linear regression analysis; patient treatment; predictive model; sickle cell anemia; Accuracy; Artificial neural networks; Condition monitoring; Failure analysis; Linear regression; Medical treatment; Patient monitoring; Pattern analysis; Pattern recognition; Predictive models;

fLanguage

English

Publisher

ieee

Conference_Titel

[Engineering in Medicine and Biology, 1999. 21st Annual Conference and the 1999 Annual Fall Meetring of the Biomedical Engineering Society] BMES/EMBS Conference, 1999. Proceedings of the First Joint

Conference_Location

Atlanta, GA

ISSN

1094-687X

Print_ISBN

0-7803-5674-8

Type

conf

DOI

10.1109/IEMBS.1999.802465

Filename

802465