Human-centred artificial intelligence for mobile health sensing: challenges and opportunities
Advances in wearable sensing and mobile computing have enabled the collection of health
and well-being data outside of traditional laboratory and hospital settings, paving the way for …
and well-being data outside of traditional laboratory and hospital settings, paving the way for …
A simplicial epidemic model for COVID-19 spread analysis
Networks allow us to describe a wide range of interaction phenomena that occur in complex
systems arising in such diverse fields of knowledge as neuroscience, engineering, ecology …
systems arising in such diverse fields of knowledge as neuroscience, engineering, ecology …
A survey on data-driven covid-19 and future pandemic management
The COVID-19 pandemic has resulted in more than 440 million confirmed cases globally
and almost 6 million reported deaths as of March 2022. Consequently, the world …
and almost 6 million reported deaths as of March 2022. Consequently, the world …
AI for development: Implications for theory and practice
C Bjola - Oxford Development Studies, 2022 - Taylor & Francis
The arrival of AI technology promises to add a fascinating new chapter to development
theory and practice. Current studies have made good progress in examining the potential …
theory and practice. Current studies have made good progress in examining the potential …
Differentiable agent-based epidemiology
Mechanistic simulators are an indispensable tool for epidemiology to explore the behavior of
complex, dynamic infections under varying conditions and navigate uncertain environments …
complex, dynamic infections under varying conditions and navigate uncertain environments …
[HTML][HTML] Revealing geographic transmission pattern of COVID-19 using neighborhood-level simulation with human mobility data and SEIR model: A Case Study of …
Direct human physical contact accelerates COVID-19 transmission. Smartphone mobility
data has emerged as a valuable data source for revealing fine-grained human mobility …
data has emerged as a valuable data source for revealing fine-grained human mobility …
Human mobility modeling during the COVID-19 pandemic via deep graph diffusion infomax
Abstract Non-Pharmaceutical Interventions (NPIs), such as social gathering restrictions,
have shown effectiveness to slow the transmission of COVID-19 by reducing the contact of …
have shown effectiveness to slow the transmission of COVID-19 by reducing the contact of …
Estimating geographic spillover effects of COVID-19 policies from large-scale mobility networks
Many policies in the US are determined locally, eg, at the county-level. Local policy regimes
provide flexibility between regions, but may become less effective in the presence of …
provide flexibility between regions, but may become less effective in the presence of …
Analysis of performance improvements and bias associated with the use of human mobility data in covid-19 case prediction models
The COVID-19 pandemic has mainstreamed human mobility data into the public domain,
with research focused on understanding the impact of mobility reduction policies as well as …
with research focused on understanding the impact of mobility reduction policies as well as …
GAT-MF: Graph Attention Mean Field for Very Large Scale Multi-Agent Reinforcement Learning
Recent advancements in reinforcement learning have witnessed remarkable achievements
by intelligent agents ranging from game-playing to industrial applications. Of particular …
by intelligent agents ranging from game-playing to industrial applications. Of particular …