ArticleHealthcare (Basel, Switzerland)2020
What Can COVID-19 Teach Us about Using AI in Pandemics?
Article in Healthcare (Basel, Switzerland), 2020. 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, 22 citations in OpenAlex.
- A Survey on COVID-19 Data Analysis Using AI, IoT, and Social Media.Sensors (Basel, Switzerland) · 2023Review
- COVID-19 and beyond: leveraging artificial intelligence for enhanced outbreak control.Frontiers in artificial intelligence · 2023Review
- Applying an Improved Stacking Ensemble Model to Predict the Mortality of ICU Patients with Heart Failure.Journal of clinical medicine · 2022Article
- The medical and societal impact of big data analytics and artificial intelligence applications in combating pandemics: A review focused on Covid-19.Social science & medicine (1982) · 2022Review
- A Narrative Review of Innovative Responses During the COVID-19 Pandemic in 2020.International journal of public health · 2022Review
- Computational Intelligence-Based Model for Mortality Rate Prediction in COVID-19 Patients.International journal of environmental research and public health · 2021Article
- The Enigmatic COVID-19 Vulnerabilities and the Invaluable Artificial Intelligence (AI).Journal of multidisciplinary healthcare · 2021Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The COVID-19 pandemic put significant strain on societies and their resources, with the healthcare system and workers being particularly affected. Artificial Intelligence (AI) offers the unique possibility of improving the response to a pandemic as it emerges and evolves. Here, we utilize the WHO framework of a pandemic evolution to analyze the various AI applications. Specifically, we analyzed AI from the perspective of all five domains of the WHO pandemic response. To effectively review the current scattered literature, we organized a sample of relevant literature from various professional and popular resources. The article concludes with a consideration of AI's weaknesses as key factors affecting AI in future pandemic preparedness and response.
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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.