Analyzing Maternal Health in Nigeria using Machine Learning

Local Chapter Kano, Nigeria Chapter

Coordinated byNigeria ,

Alamin Musa Magaga

Status: Ongoing

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.

The problem.

The statistics paint a grim picture of maternal health in Nigeria. The latest World Health Organization (WHO) data reveals that Nigeria accounts for over 34% of global maternal deaths. The lifetime risk of a Nigerian woman dying during pregnancy, childbirth, postpartum, or after an abortion is an alarming one in 22, in stark contrast to the figure of one in 4,900 in developed countries. The situation is exacerbated by the lack of accessible medical facilities and healthcare resources in many rural communities across the 36 states of the country. Insufficient medical personnel and outdated infrastructure further hinder the provision of adequate care. Tragically, there have been instances of pregnant women losing their lives while travelling from their homes to distant medical facilities, highlighting the critical need for accessible and timely healthcare services.

Project goals.

The project goals are:- Provide accurate risk prediction for maternal health complications based on advanced AI algorithms. - Analyze the latest maternal health data to identify patterns, trends, and contributing factors. - Generate evidence-based prevention recommendations for healthcare providers and policymakers. - Develop a user-friendly web app to provide accessible risk assessments, data analysis, and prevention recommendations. - Design an intuitive dashboard to visualize maternal health indicators and insights, enabling effective decision-making. - Contribute to improving overall maternal health outcomes in Nigeria by facilitating targeted interventions and enhancing the accessibility of valuable insights.

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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