2024 Proceedings

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Browsing 2024 Proceedings by Author "Ahmad I.I."

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    Open Access
    Geo-Semantic Analysis of Medical Research Trends in Nigeria
    (MIRG, 2024-11-25) Ahmad I.I.; Anthony, S.; Olubayo A.; Bashirudeen I.; David A.
    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.
  • Item
    Open Access
    Leveraging Geo-Nlp for Enhanced Antiretroviral Drug Distribution in Nigeria: Insights from Social Media and News Data
    (MIRG, 2024-11-25) Bashirudeen O.I.; Olubayo A.; Anthony S.; Ahmad I.I.
    Faced with over 1.9 million HIV/AIDS cases, Nigeria’s need for efficient antiretroviral therapy (ART) distribution is crucial as conventional drug distribution methods are restrained by logistical issues and data scarcity and thus require innovative solutions. This study employs Geographic Natural Language Processing (Geo-NLP) to analyse social media and news content, offering novel insights into public discourse on HIV/AIDS and ART across Nigeria. Using a custom Named-Entity Recognition (NER) model to process data from NairaLand and major newspapers, the research uncovers geographical patterns in HIV/AIDS-related conversations, achieving a significant model performance with an overall F1-Score of 83.27%. Other analysis done scraopped text data spotlights areas with more discussions on HIV/AIDS, suggesting areas like Bauchi, Jos, and Ibadan as priority sites for targeted ART distribution interventions. This approach aims to refine ART distribution strategies and sets a precedent for employing Geo-NLP in public health planning. Despite its brevity, the study underscores the potential of integrating Geo-NLP with traditional data to enhance healthcare delivery in Nigeria, paving the way for a more effective public health interventions against the HIV/AIDS epidemic.