Human-in-the-loop reinforcement learning: A survey and position on requirements, challenges, and opportunities

CO Retzlaff, S Das, C Wayllace, P Mousavi… - Journal of Artificial …, 2024 - jair.org
Artificial intelligence (AI) and especially reinforcement learning (RL) have the potential to
enable agents to learn and perform tasks autonomously with superhuman performance …

An evaluation of prospective COVID-19 modelling studies in the USA: from data to science translation

K Nixon, S **dal, F Parker, NG Reich… - The Lancet Digital …, 2022 - thelancet.com
Infectious disease modelling can serve as a powerful tool for situational awareness and
decision support for policy makers. However, COVID-19 modelling efforts faced many …

The US COVID-19 Trends and Impact Survey: Continuous real-time measurement of COVID-19 symptoms, risks, protective behaviors, testing, and vaccination

JA Salomon, A Reinhart, A Bilinski… - Proceedings of the …, 2021 - National Acad Sciences
The US COVID-19 Trends and Impact Survey (CTIS) is a large, cross-sectional, internet-
based survey that has operated continuously since April 6, 2020. By inviting a random …

JUE Insight: Measuring movement and social contact with smartphone data: a real-time application to COVID-19

V Couture, JI Dingel, A Green, J Handbury… - Journal of Urban …, 2022 - Elsevier
Tracking human activity in real time and at fine spatial scale is particularly valuable during
episodes such as the COVID-19 pandemic. In this paper, we discuss the suitability of …

Improved deep convolutional neural networks using chimp optimization algorithm for Covid19 diagnosis from the X-ray images

C Cai, B Gou, M Khishe, M Mohammadi… - Expert Systems with …, 2023 - Elsevier
Abstract Applying Deep Learning (DL) in radiological images (ie, chest X-rays) is emerging
because of the necessity of having accurate and fast COVID-19 detectors. Deep …

Where to locate COVID‐19 mass vaccination facilities?

D Bertsimas, V Digalakis Jr, A Jacquillat… - Naval Research …, 2022 - Wiley Online Library
The outbreak of COVID‐19 led to a record‐breaking race to develop a vaccine. However,
the limited vaccine capacity creates another massive challenge: how to distribute vaccines …

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the US

EY Cramer, EL Ray, VK Lopez, J Bracher, A Brennen… - Medrxiv, 2021 - medrxiv.org
Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United
States have served as a visible and important communication channel between the scientific …

An open repository of real-time COVID-19 indicators

A Reinhart, L Brooks, M Jahja… - Proceedings of the …, 2021 - National Acad Sciences
The COVID-19 pandemic presented enormous data challenges in the United States. Policy
makers, epidemiological modelers, and health researchers all require up-to-date data on the …

[HTML][HTML] Machine learning research towards combating COVID-19: Virus detection, spread prevention, and medical assistance

O Shahid, M Nasajpour, S Pouriyeh, RM Parizi… - Journal of Biomedical …, 2021 - Elsevier
COVID-19 was first discovered in December 2019 and has continued to rapidly spread
across countries worldwide infecting thousands and millions of people. The virus is deadly …

Forecasting COVID-19 and analyzing the effect of government interventions

ML Li, HT Bouardi, OS Lami, TA Trikalinos… - Operations …, 2023 - pubsonline.informs.org
We developed DELPHI, a novel epidemiological model for predicting detected cases and
deaths in the prevaccination era of the COVID-19 pandemic. The model allows for …