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Emmanuel Owiredu Odame

Statistics and Actuarial Science

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Research Summary

(inferred from publications by AI)

The researcher has conducted extensive work across diverse fields, integrating advanced methodologies to address challenges in fraud detection (machine learning), water quality assessment, Hepatitis B virus studies, COVID-19 epidemiology, eating disorders, and neonatal respiratory health.

Research Themes

All Papers

A supervised machine learning algorithm for detecting and predicting fraud in credit card transactions(2023)
Supervised Machine Learning Algorithm Approach to Detecting and Predicting Fraud in Credit Card Transactions(2022)
Assessing the Influence of Hand-Dug Well Features and Management on Water Quality(2024)
Prevalence of Helicobacter pylori, Salmonella typhi, Plasmodium falciparum, and Toxoplasma gondii infections and levels of liver function markers among Hepatitis B Virus infected Ghanaians: A cross-sectional study in the Greater Accra Region(2025)
Social Response and Measles Dynamics(2023)
Body Image: a Cross-sectional Study of the Perception and Practices of Women After Delivery(2024)
Body image: a cross-sectional study of the perception and practices of women after delivery(2025)
Evaluating the Effectiveness of an Evidence-Based Practice in Neonatal Resuscitation among Birth Asphyxiated Newborns in a Developing Country(2024)

Collaboration Network

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About This Profile

This profile is generated from publicly available publication metadata and is intended for research discovery purposes. Themes, summaries, and trajectories are inferred computationally and may not capture the full scope of the lecturer's work. For authoritative information, please refer to the official KNUST profile.