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Re-imagining health and well-being in low resource African settings using an augmented AI system and a 3D digital twin

arXiv 2306.01772 ↗First posted 29 May 2023cs.AIcited by 0

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Abstract (arXiv)

This paper discusses and explores the potential and relevance of recent developments in artificial intelligence (AI) and digital twins for health and well-being in low-resource African countries. We use the case of public health emergency response to disease outbreaks and epidemic control. There is potential to take advantage of the increasing availability of data and digitization to develop advanced AI methods for analysis and prediction. Using an AI systems perspective, we review emerging trends in AI systems and digital twins and propose an initial augmented AI system architecture to illustrate how an AI system can work with a 3D digital twin to address public health goals. We highlight scientific knowledge discovery, continual learning, pragmatic interoperability, and interactive explanation and decision-making as essential research challenges for AI systems and digital twins.

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References · 6

  1. 2021Mind the Gap: Assessing Temporal Generalization in Neural Language Modelscited by 226
  2. 2022On scientific understanding with artificial intelligencecited by 68
  3. 2021Hybrid Intelligencecited by 55
  4. 2019Evaluating time series forecasting models: An empirical study on performance estimation methodscited by 52
  5. 2020Directions for Explainable Knowledge-Enabled Systemscited by 10
  6. 2020Foundations of Explainable Knowledge-Enabled Systemscited by 6

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