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Artificial Intelligence for Public Health Surveillance in Africa: Applications and Opportunities

arXiv 2408.02575 ↗First posted 5 Aug 2024cs.LG cs.CLcited by 1

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Abstract (arXiv)

Artificial Intelligence (AI) is revolutionizing various fields, including public health surveillance. In Africa, where health systems frequently encounter challenges such as limited resources, inadequate infrastructure, failed health information systems and a shortage of skilled health professionals, AI offers a transformative opportunity. This paper investigates the applications of AI in public health surveillance across the continent, presenting successful case studies and examining the benefits, opportunities, and challenges of implementing AI technologies in African healthcare settings. Our paper highlights AI's potential to enhance disease monitoring and health outcomes, and support effective public health interventions. The findings presented in the paper demonstrate that AI can significantly improve the accuracy and timeliness of disease detection and prediction, optimize resource allocation, and facilitate targeted public health strategies. Additionally, our paper identified key barriers to the widespread adoption of AI in African public health systems and proposed actionable recommendations to overcome these challenges.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 6 of its 219 references that are in the map. First posted on arXiv 5 Aug 2024.

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6 of 219 references.

References · 6

  1. 2024Analyzing Diversity in Healthcare LLM Research: A Scientometric Perspectivecited by 4
  2. 2022Improved Healthcare Access in Low-resource Regions: A Review of Technological Solutionscited by 3
  3. 2023Redesigning Electronic Health Record Systems to Support Developing Countriescited by 2
  4. 2024A Short Survey of Human Mobility Prediction in Epidemic Modeling from Transformers to LLMscited by 2
  5. 2020Visualization and machine learning for forecasting of COVID-19 in Senegalcited by 1
  6. 2024Machine Learning-based NLP for Emotion Classification on a Cholera X Datasetcited by 1

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