Geo-Semantic Analysis of Medical Research Trends in Nigeria
Keywords: Named Entity Recognition, Natural language Processing, Global Health, Medical Research, Health Policy, Geo-semantics
Abstract: In the context of a rapidly evolving global health landscape, this study aims to cast light on the focal points and regional intricacies of medical research in Nigeria. It addresses the critical need to align medical research with health policies, responding to the dynamic health requirements of Nigeria's diverse population. Utilizing a Geo-semantic approach, the research melds Geospatial Analysis with the advanced capabilities of Natural Language Processing. This methodology was applied to analyze and visually interpret Nigerian medical research's thematic and geographic trends based on articles from the PubMed database. The study uncovered distinct regional focuses and collaborative networks in medical research, underscoring the importance of aligning research efforts with the prevalent health challenges. The study found emergent challenges like COVID-19 and epidemiological studies receiving optimum attention, while prevalent health challenges like health insurance and neglected tropical diseases were on the dwindling end of research interest. These findings provide a blueprint for improving the effectiveness of medical research and healthcare policy in Nigeria, offering significant insights for strategic planning and resource allocation in the health sector. Moreover, this innovative approach demonstrates the feasibility and value of integrating NLP and geospatial analysis in medical research. It opens new avenues for low- and middle-income countries to derive insights and enhance their healthcare planning strategies by leveraging data from unstructured sources.
Submission Number: 41
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