Jaundice Detection System Using Physiological Characteristics

Ekereke, Layefa *

Department of Mathematical Sciences, Faculty of Basic and Applied Sciences, University of Africa, Toru-Orua, Bayelsa State, Nigeria.

Prince O. Asagba

Department of Computer Science, Faculty of Sciences, University of Port-Harcourt, Rivers State, Nigeria.

*Author to whom correspondence should be addressed.


Abstract

Jaundice is the abnormal accumulation of Bilirubin in the blood, constant checking of their content level in the blood of new born children is vital as going for Anti-natal because its effect is dangerous and irreversible. At the moment, the standard method to determining the concentration of bilirubin in neonates is Laboratory Blood Test (TSB) test and this method can be traumatic for babies due to the constant blood extraction. Our goal in this research is to use hybridized machine learning techniques to develop a jaundice detection system using all the possible physiological characteristics or symptoms. The developed jaundice detection system is capable of detecting the presence of jaundice in neonate non-invasively, it also has a 0.07% standard error coefficient and a Percentage Value of 0.001 when the outcome was compared to TSB of all Test and Validation samples.

Keywords: Bilirubin, skin, gestation age, eye colour, jaundice


How to Cite

Layefa, Ekereke, and Prince O. Asagba. 2021. “Jaundice Detection System Using Physiological Characteristics”. Asian Journal of Research in Computer Science 12 (2):30-39. https://doi.org/10.9734/ajrcos/2021/v12i230279.

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