Using the Gamma Regression Model in Diagnosing Neonatal Jaundice  among Newborns in Diyala Province

Gheada Ibrahim Sheab; Lubna Jaafar Hussein Ibrahim; Nawal Muhammad Yaqoub  Khalil; Sura Anwar Jameel

doi:10.62383/algoritma.v3i6.780

Authors

Gheada Ibrahim Sheab University of Diyala
Lubna Jaafar Hussein Ibrahim University of Diyala
Nawal Muhammad Yaqoub Khalil University of Diyala
Sura Anwar Jameel Baqubah Technical Collage

DOI:

https://doi.org/10.62383/algoritma.v3i6.780

Keywords:

Newborns, Bilirubin, Jaundice, Gamma Regression, Birth weight

Abstract

This paper applies the Gamma Regression Model to determine the probability of newborns in the Diyala Province developing neonatal jaundice, or hyperbilirubinemia. This disease is prevalent, and it may be severe due to the large amount of unconjugated bilirubin in the blood. The aim of the study was to test the relationship between the levels of bilirubin and a set of independent variables, including the weight of birth, gestational age, and the proportion of red blood cells (PVC). 67 worth of data regarding neonatal cases was collected, and the outcome was that the model fitted well. The findings further indicated that whereas the influence of PVC was significant and positive on the bilirubin level, lower gestational age and less weight at birth had significant negative influence. As the results of the study indicate, the Gamma Regression Model is an effective tool to assess medical data and predict critical scenarios, which assists a clinician with the timely and accurate decision-making.

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