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 …
PD Yu, CW Tan, HL Fu - IEEE Journal of Selected Topics in …, 2022 - ieeexplore.ieee.org
We study the epidemic source detection problem in contact tracing networks modeled as a graph-constrained maximum likelihood estimation problem using the susceptible-infected …
Mechanistic simulators are an indispensable tool for epidemiology to explore the behavior of complex, dynamic infections under varying conditions and navigate uncertain environments …
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 …
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 …
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 …
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 …
The COVID-19 pandemic has spurred an unprecedented demand for interventions that can reduce disease spread without excessively restricting daily activity, given negative impacts …
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 …