Advanced Statistical Modelling in Neonatal Outcome Prediction
Keywords:
Predictive Modelling, Data Science, Neonatal Hypoxia, Medical Statistics, Neonatal Outcomes, Nucleated Red Blood CellsAbstract
Neonatal complications are a major cause of newborn morbidity and mortalityworldwide. Nucleated Red Blood Cells (NRBCs) are important hematological biomarkers of fetal hypoxia and neonatal stress. Statistical modelling and predictive data analysis canfacilitate early identification of high-risk neonates
References
Agresti, A. (2018). Statistical Methods for the Social Sciences (5th ed.). Pearson.
Altman, D. G. (1991). Practical Statistics for Medical Research. Chapman and Hall.
Bishop, C. M. (2006). Pattern Recognition and Machine Learning. Springer.
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Published
2026-01-15
How to Cite
Dr. A. Vani, P. Srivyshnavi , Dr. P.Palavardhan, Dr. M. Bhupathi Naidu. (2026). Advanced Statistical Modelling in Neonatal Outcome Prediction . Journal of Computational Analysis and Applications (JoCAAA), 35(1), 1237–1248. Retrieved from https://eudoxuspress.com/index.php/pub/article/view/5487
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