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A robust machine learning framework for diabetes prediction (2021)
Conference Proceeding
Olisah, C., Adeleye, O., Smith, L., & Smith, M. (2022). A robust machine learning framework for diabetes prediction. In Proceedings of the Future Technologies Conference (FTC) 2021 (775-792). https://doi.org/10.1007/978-3-030-89880-9_58

Diabetes mellitus is a metabolic disorder characterized by hyperglycemia which results from the inadequacy of the body to secret and responds to insulin. If not properly managed or diagnosed on time, diabetes can pose a risk to vital body organs such... Read More about A robust machine learning framework for diabetes prediction.

Data-driven approach to COVID-19 infection forecast for Nigeria using negative binomial regression model (2021)
Book Chapter
Olisah, C. C., Ilori, O. O., Adelaja, K., Usip, P. U., Uzoechi, L. O., Adeyanju, I. A., & Odumuyiwa, V. T. (2021). Data-driven approach to COVID-19 infection forecast for Nigeria using negative binomial regression model. In Data Science for COVID-19 (583-596). Elsevier. https://doi.org/10.1016/b978-0-12-824536-1.00002-2

COVID-19: the new wave of a global pandemic, is bringing about an increasing number of scientific efforts aimed at enabling governments to make informed decisions. In this paper, we explore the negative binomial regression model from the family of ge... Read More about Data-driven approach to COVID-19 infection forecast for Nigeria using negative binomial regression model.