ReviewJournal of medical systems2020
Utility of Artificial Intelligence Amidst the COVID 19 Pandemic: A Review.
Review in Journal of medical systems, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers, 1 of them a synthesis that pooled it.
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
35 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Digital imaging, technologies and artificial intelligence applications during COVID-19 pandemic.Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society · 2021Pooled it
- Machine learning algorithms for predicting COVID-19 mortality in Ethiopia.BMC public health · 2024Article
- Short- and Long-Term Predicted and Witnessed Consequences of Digital Surveillance During the COVID-19 Pandemic: Scoping Review.JMIR public health and surveillance · 2024Article
- Deep learning in public health: Comparative predictive models for COVID-19 case forecasting.PloS one · 2024Article
- PRedicting the EVolution of SubjectIvE Cognitive Decline to Alzheimer's Disease With machine learning: the PREVIEW study protocol.BMC neurology · 2023Article
- A Survey on COVID-19 Data Analysis Using AI, IoT, and Social Media.Sensors (Basel, Switzerland) · 2023Review
- Determining human-coronavirus protein-protein interaction using machine intelligence.Medicine in novel technology and devices · 2023Article
- Emerging technologies for COVID (ET-CoV) detection and diagnosis: Recent advancements, applications, challenges, and future perspectives.Biomedical signal processing and control · 2023Review
- Comparing artificial neural network training algorithms to predict length of stay in hospitalized patients with COVID-19.BMC infectious diseases · 2022Article
- Artificial Intelligence and COVID-19: A Systematic umbrella review and roads ahead.Journal of King Saud University. Computer and information sciences · 2022Review
- Surveillance of emerging infectious diseases for biosecurity.Science China. Life sciences · 2022Review
- An original deep learning model using limited data for COVID-19 discrimination: A multicenter study.Medical physics · 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
- Artificial Intelligence for COVID-19 Detection in Medical Imaging-Diagnostic Measures and Wasting-A Systematic Umbrella Review.Journal of clinical medicine · 2022Review
- Domain Shifts in Machine Learning Based Covid-19 Diagnosis From Blood Tests.Journal of medical systems · 2022Article
- Comparing machine learning algorithms for predicting COVID-19 mortality.BMC medical informatics and decision making · 2022Article
- Developing an artificial neural network for detecting COVID-19 disease.Journal of education and health promotion · 2022Article
- Using artificial intelligence technology to fight COVID-19: a review.Artificial intelligence review · 2022Article
- Predicting COVID-19 community infection relative risk with a Dynamic Bayesian Network.Frontiers in public health · 2022Article
- Online Disease Identification and Diagnosis and Treatment Based on Machine Learning Technology.Journal of healthcare engineering · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The term machine learning refers to a collection of tools used for identifying patterns in data. As opposed to traditional methods of pattern identification, machine learning tools relies on artificial intelligence to map out patters from large amounts of data, can self-improve as and when new data becomes available and is quicker in accomplishing these tasks. This review describes various techniques of machine learning that have been used in the past in the prediction, detection and management of infectious diseases, and how these tools are being brought into the battle against COVID-19. In addition, we also discuss their applications in various stages of the pandemic, the advantages, disadvantages and possible pit falls.
Indexed as
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.