Published on by Top Teachers

Innovative Research Award

Samuel Odoom

Mampong Technical College of Education, Ghana

Samuel Odoom
Affiliation Mampong Technical College of Education
Country Ghana
Scopus ID 6507729911
Documents 21
Citations 286
h-index 9
Subject Area Information Technology
Event Top Teachers Awards
ORCID 0009-0003-3551-5370
Google Scholar cqeBuLYAAAAJ

Samuel Odoom is a researcher and educator specializing in Artificial Intelligence, Machine Learning, and Data-Driven Decision Support Systems. His work focuses on applying advanced predictive modeling techniques, including ensemble learning, explainable AI, and psychometric analytics, to address critical challenges in healthcare and education. He has contributed to research on disease risk prediction, student success modeling through emotional intelligence and behavioral traits, and intelligent systems for evidence-based decision-making. Odoom is committed to developing ethical, interpretable, and impactful AI solutions that bridge research, policy, and practice for sustainable societal advancement.[1]

Abstract

This article presents the research and scholarly contributions of Samuel Odoom, nominated for the Innovative Research Award in recognition of his work in artificial intelligence, machine learning, and data-driven decision support. His research addresses pressing challenges in healthcare and education, with a focus on predictive modeling and explainable AI. With 21 documents, 286 citations, and an h-index of 9, Odoom’s work demonstrates measurable academic impact and practical relevance. His commitment to ethical and interpretable AI aligns with the goals of the Top Teachers Awards, making him a strong candidate for this recognition.[1]

Keywords

Artificial Intelligence, Machine learning, Data Analytics, Public Health, Predictive Modeling, Explainable AI, Educational Technology.

Introduction

The integration of artificial intelligence and machine learning into critical sectors such as healthcare and education has opened new frontiers for evidence-based decision-making. Samuel Odoom has been at the forefront of this movement, leveraging predictive analytics and explainable AI to address real-world problems in Ghana and beyond. His work spans disease risk prediction, student success modeling through emotional intelligence, and intelligent systems design. This article provides a comprehensive overview of his research profile, contributions, and impact, with a focus on his suitability for the Innovative Research Award.[1][2]

Research Profile

Samuel Odoom is currently pursuing a PhD in Information Technology at Ghana Communication Technology University, building on an MPhil from Kwame Nkrumah University of Science and Technology and a BSc in Information Technology Education from the University of Education, Winneba-Kumasi. His academic training is complemented by extensive leadership experience, including roles as Form Master at Islamic Senior High School, Wa, and Editorial Board Chairman of INFOTESS. Odoom’s research is characterized by interdisciplinary collaboration, with publications that span healthcare outcomes, HIV self-esteem assessment, and traditional medicine training, often employing data mining and machine learning techniques.[1][2]

Research Contributions

Samuel Odoom’s contributions are rooted in the application of AI to address systemic challenges in healthcare and education. His work on tuberculosis treatment outcomes provided critical insights into factors affecting patient recovery in the Ashanti region of Ghana[3]. In the domain of public health, he co-authored a study on self-esteem among adolescents living with HIV, highlighting psychological dimensions of care[4]. More recently, his collaboration on training traditional bonesetters in fracture management demonstrates a commitment to integrating modern medical principles with local practices[5]. These projects reflect his ability to translate complex data into actionable insights, a hallmark of his research philosophy.

Publications

Samuel Odoom has authored or co-authored 21 documents indexed in Scopus, with 286 citations and an h-index of 9. His key publications include a retrospective study on tuberculosis treatment outcomes in Ghana[3], an assessment of self-esteem among adolescents living with HIV[4], and a proof-of-concept study on training traditional bonesetters in fracture treatment[5]. These works demonstrate his interdisciplinary approach and commitment to improving health outcomes through data-driven research.

Samuel Odoom has authored or co-authored 21 documents indexed in Scopus, with 286 citations and an h-index of 9. Key publications include:

  • Agyare, S. A., Osei, F. A., Odoom, S. F., Mensah, N. K., Amanor, E., et al. (2021). Treatment outcomes and associated factors in tuberculosis patients at Atwima Nwabiagya district, Ashanti region, Ghana: a ten‐year retrospective study. Tuberculosis Research and Treatment, 2021, 9952806.
  • Agyemang, E. O., Dapaah, J. M., Osei, F. A., Appiah, S. C. Y., Mensah, N. K., Odoom, S. F. (2020). Self-esteem assessment among adolescents living with HIV and seeking healthcare at Komfo Anokye Teaching Hospital-Kumasi, Ghana. Journal of the International Association of Providers of AIDS Care, 19, 2325958220976828.
  • Konadu-Yeboah, D., Yempabe, T., Buunaaim, A. D. B., Konadu, P., Owusu, R., Odoom, S. F. (2023). Training traditional bonesetters in basic principles of fracture treatment: a proof of concept in Ghana. JBJS, 105(24), 1995-2001.

Research Impact

The impact of Samuel Odoom’s work is evidenced by 286 citations across his 21 documents, reflecting the relevance of his research to both academic and practitioner communities. His studies on tuberculosis treatment outcomes and HIV self-esteem have informed public health policies in Ghana, while his recent work on bonesetter training bridges traditional and modern healthcare. In education, his focus on emotional intelligence and behavioral traits in student success modeling has implications for personalized learning interventions. Samuel Odoom’s research is regularly presented at seminars, including the Microsoft Elevate for Educators and the Research Clinic at KNUST, demonstrating his engagement with the broader scholarly community.[1][2]

Award Suitability

Samuel Odoom exemplifies the qualities of an innovative researcher: technical excellence, interdisciplinary collaboration, and a clear commitment to societal impact. His work aligns with the United Nations Sustainable Development Goals, particularly in health (SDG 3) and education (SDG 4). The Top Teachers Awards recognize educators who go beyond the classroom, and Samuel Odoom’s research-driven approach to improving healthcare and educational outcomes makes him an ideal candidate. His leadership roles, including course representation and editorial board chairmanship, further demonstrate his capacity to influence and mentor peers.[1][2]

Conclusion

This article has provided a comprehensive overview of Samuel Odoom’s research profile, contributions, and impact. His work in artificial intelligence, machine learning, and data-driven decision support has addressed critical challenges in healthcare and education, with measurable outcomes in citations and practical applications. Odoom’s commitment to ethical, interpretable, and impactful AI positions him as a leader in his field. His nomination for the Innovative Research Award is well-supported by his scholarly output, interdisciplinary collaborations, and dedication to bridging research, policy, and practice.[1][2]

11. References

  1. Elsevier. (n.d.). Scopus author details: Samuel Odoom, Author ID 6507729911. Scopus. https://www.scopus.com/pages/authors/6507729911
  2. Google Scholar. (n.d.). Samuel Odoom – Google Scholar Profile. https://scholar.google.com/citations?user=cqeBuLYAAAAJ&hl=en&oi=sra
  3. Agyare, S. A., Osei, F. A., Odoom, S. F., Mensah, N. K., Amanor, E., et al. (2021). Treatment outcomes and associated factors in tuberculosis patients at Atwima Nwabiagya district, Ashanti region, Ghana: a ten‐year retrospective study. Tuberculosis Research and Treatment, 2021, 9952806. https://doi.org/10.1155/2021/9952806
  4. Agyemang, E. O., Dapaah, J. M., Osei, F. A., Appiah, S. C. Y., Mensah, N. K., Odoom, S. F. (2020). Self-esteem assessment among adolescents living with HIV and seeking healthcare at Komfo Anokye Teaching Hospital-Kumasi, Ghana. Journal of the International Association of Providers of AIDS Care (JIAPAC), 19, 2325958220976828. https://doi.org/10.1177/2325958220976828
  5. Konadu-Yeboah, D., Yempabe, T., Buunaaim, A. D. B., Konadu, P., Owusu, R., Odoom, S. F. (2023). Training traditional bonesetters in basic principles of fracture treatment: a proof of concept in Ghana. Journal of Bone and Joint Surgery, 105(24), 1995-2001. https://doi.org/10.2106/jbjs.22.01304
Samuel Odoom | Information Technology | Innovative Research Award

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