The Pattern of Occurrence, Risk Factor and Biomarkers Associated with Leiomyoma in Calabar, Nigeria
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Published:
2024-04-19
Keywords:
Leiomyoma, biomarkers, Immunohistochemistry, artificial neural network
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Abstract
BACKGROUND
Uterine fibroid is the commonest gynecologic tumour in women of reproductive age
but there is a disparity in research to understand the aetiology and risk factors of the disease
in Calabar. This study analyzed the clinical and histopathological characteristics of subjects
and used an artificial neural network (ANN) to predict the risk factors/biomarkers of
leiomyoma.
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© 2024 The authors. This work is licensed under the Creative Commons Attribution 4.0 International License (CC BY 4.0).
How to Cite
The Pattern of Occurrence, Risk Factor and Biomarkers Associated with Leiomyoma in Calabar, Nigeria. (2024). African Journal of Health Sciences, 35(5), 628-638. https://ojs.ajhsjournal.or.ke/index.php/home/article/view/238