ArticleFrontiers in public health2021
Exploring Feasibility of Multivariate Deep Learning Models in Predicting COVID-19 Epidemic.
Article in Frontiers in public health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed.
- Predicting COVID-19 using lioness optimization algorithm and graph convolution network.Soft computing · 2023Article
- Content and sentiment surveillance (CSI): A critical component for modeling modern epidemics.Frontiers in public health · 2023Article
- Deep learning for Covid-19 forecasting: State-of-the-art review.Neurocomputing · 2022Article
- Social Efficiency of Public Transportation Policy in Response to COVID-19: Model Development and Application to Intercity Buses in Seoul Metropolitan Area.International journal of environmental research and public health · 2022Article
- An incremental learning approach to prediction models of SEIRD variables in the context of the COVID-19 pandemic.Health and technology · 2022Article
- Risk of COVID-19 Infection in Public Transportation: The Development of a Model.International journal of environmental research and public health · 2021Article
- Spatio-temporal prediction of the COVID-19 pandemic in US counties: modeling with a deep LSTM neural network.Scientific reports · 2021Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
PubMed holds no abstract for this paper.
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Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.