Analyzing Maternal Health in Nigeria using Machine Learning

Local Chapter Kano, Nigeria Chapter

Coordinated by Nigeria ,

Project background.

Maternal health is a pressing concern in Nigeria, with an alarming rate of maternal mortalities. Currently, Nigeria has one of the highest maternal mortality rates in the world, with approximately 512 maternal mortalities per 100,000 births. This devastating figure underscores the urgent need for effective interventions to improve maternal health outcomes. Additionally, the impact of the COVID-19 pandemic has further exacerbated the challenges faced in maternal healthcare, severely impacting the healthcare system and exacerbating the already dire situation.

Project plan.

  • Week 1

    Data collection:
    Collect relevant maternal health data from reliable sources.

  • Week 2

    EDA and feature selection:
    Prepare and clean the collected data for analysis.
    Conduct exploratory data analysis (EDA) to understand the data and identify initial insights.

  • Week 3

    Model building: Explore various AI models suitable for risk prediction in maternal health. Select and develop the most appropriate AI model based on the data analysis. Train and fine-tune the AI model using the prepared data. Validate the model’s performance and evaluate its accuracy and predictive capabilities.

  • Week 4

    Dashboard: Implement interactive data visualization components for the dashboard to showcase maternal health indicators and insights.

  • Week 5

    Web app: Develop a user-friendly web app with a clear interface for risk prediction, data analysis, and prevention recommendations.

  • Week 6

    Project documentation and testing : Test the web app and dashboard to ensure the functionality, usability, and accuracy of the generated insights. Incorporate feedback and make necessary refinements to improve the user experience. Publish the web app and dashboard for public access and utilization. Document the project, including methodologies, findings, and recommendations.

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