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article · Frontiers in Artificial Intelligence

Assessing the potential for application of machine learning in predicting weather-sensitive waterborne diseases in selected districts of Tanzania

20252 citationsOpen accessMuslim University Of Morogoro

Abstract

The study highlights frontline health workers' perceived barriers to ML adoption and suggests that gender influences awareness and engagement with AI and ML technologies. Strengthening technical capacity, improving data quality, and fostering cross-sector collaboration are critical for successful AI/ML integration. These insights offer a roadmap for resilience to WSWDs in developing countries like Tanzania through data-driven technologies.

Research topics

  • COVID-19 epidemiological studies
  • COVID-19 diagnosis using AI
  • Data-Driven Disease Surveillance

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DOI: 10.3389/frai.2025.1597727

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