Privacy-enhancing digital contact tracing with machine learning for pandemic response: A comprehensive review
The rapid global spread of the coronavirus disease (COVID-19) has severely impacted daily
life worldwide. As potential solutions, various digital contact tracing (DCT) strategies have …
life worldwide. As potential solutions, various digital contact tracing (DCT) strategies have …
Contagion source detection in epidemic and infodemic outbreaks: Mathematical analysis and network algorithms
CW Tan, PD Yu - Foundations and Trends® in Networking, 2023 - nowpublishers.com
The rapid spread of infectious diseases and online rumors share similarities in terms of their
speed, scale, and patterns of contagion. Although these two phenomena have historically …
speed, scale, and patterns of contagion. Although these two phenomena have historically …
Epidemic source detection in contact tracing networks: Epidemic centrality in graphs and message-passing algorithms
We study the epidemic source detection problem in contact tracing networks modeled as a
graph-constrained maximum likelihood estimation problem using the susceptible-infected …
graph-constrained maximum likelihood estimation problem using the susceptible-infected …
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 …
Can robots do epidemiology? Machine learning, causal inference, and predicting the outcomes of public health interventions
A Broadbent, T Grote - Philosophy & Technology, 2022 - Springer
This paper argues that machine learning (ML) and epidemiology are on collision course
over causation. The discipline of epidemiology lays great emphasis on causation, while ML …
over causation. The discipline of epidemiology lays great emphasis on causation, while ML …
Deeptrace: Learning to optimize contact tracing in epidemic networks with graph neural networks
The goal of digital contact tracing is to diminish the spread of an epidemic or pandemic by
detecting and mitigating public health emergencies using digital technologies. Since the …
detecting and mitigating public health emergencies using digital technologies. Since the …
Listening to Bluetooth beacons for epidemic risk mitigation
The ongoing COVID-19 pandemic let to efforts to develop and deploy digital contact tracing
systems to expedite contact tracing and risk notification. Unfortunately, the success of these …
systems to expedite contact tracing and risk notification. Unfortunately, the success of these …
Identifying the superspreader in proactive backward contact tracing by deep learning
S Chen, PD Yu, CW Tan… - 2022 56th Annual …, 2022 - ieeexplore.ieee.org
The goal of proactive contact tracing is to diminish the spread of an epidemic by means of
contact tracing mobile apps and big data analysis. Finding superspreaders as has been …
contact tracing mobile apps and big data analysis. Finding superspreaders as has been …
Proactive contact tracing
The COVID-19 pandemic has spurred an unprecedented demand for interventions that can
reduce disease spread without excessively restricting daily activity, given negative impacts …
reduce disease spread without excessively restricting daily activity, given negative impacts …
Generalizing in the Real World with Representation Learning
T Maharaj - arXiv preprint arXiv:2210.09925, 2022 - arxiv.org
Machine learning (ML) formalizes the problem of getting computers to learn from experience
as optimization of performance according to some metric (s) on a set of data examples. This …
as optimization of performance according to some metric (s) on a set of data examples. This …