Re-imagining health and well-being in low resource African settings using an augmented AI system and a 3D digital twin
This work addresses public health problems in low-resource African countries, but it is incremental as it reviews trends and proposes an initial architecture without new empirical findings.
The paper tackles the challenge of improving health and well-being in low-resource African settings by proposing an augmented AI system integrated with a 3D digital twin for public health emergency response, focusing on disease outbreaks and epidemic control, but does not report concrete results or numbers.
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.