ArticleApplied intelligence (Dordrecht, Netherlands)2021
Forecasting COVID-19 outbreak progression using hybrid polynomial-Bayesian ridge regression model.
Article in Applied intelligence (Dordrecht, Netherlands), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 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
16 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Machine Learning Used in Communicable Disease Control: A Scoping Review.Public health reviews · 2026Pooled it
- Analysis of medical costs and two-model prediction for patients with severe mental disorders in Gansu Province, China.Frontiers in public health · 2026Article
- Machine Learning Techniques Applied to COVID-19 Prediction: A Systematic Literature Review.Bioengineering (Basel, Switzerland) · 2025Review
- Predictive Modeling for Pandemic Forecasting: A COVID-19 Study in New Zealand and Partner Countries.International journal of environmental research and public health · 2025Article
- Development of a Feed Conversion Ratio Prediction Model for Yorkshire Boars Using Cumulative Feed Intake.Animals : an open access journal from MDPI · 2025Article
- A self-driven ESN-DSS approach for effective COVID-19 time series prediction and modelling.Epidemiology and infection · 2024Article
- Uncovering hidden and complex relations of pandemic dynamics using an AI driven system.Scientific reports · 2024Article
- Highly-integrable analogue reservoir circuits based on a simple cycle architecture.Scientific reports · 2024Article
- Flow and access: Driving forces of COVID-19 spreading in the first stage around Hubei, China.PloS one · 2023Article
- Ambient air pollutants concentration prediction during the COVID-19: A method based on transfer learning.Knowledge-based systems · 2022Article
- What Is the Impact of Early and Subsequent Epidemic Characteristics on the Pre-delta COVID-19 Epidemic Size in the United States?Pathogens (Basel, Switzerland) · 2022Article
- Machine Learning-Based Research for COVID-19 Detection, Diagnosis, and Prediction: A Survey.SN computer science · 2022Article
- Quest for Optimal Regression Models in SARS-CoV-2 Wastewater Based Epidemiology.International journal of environmental research and public health · 2021Article
- Application of machine learning in the prediction of COVID-19 daily new cases: A scoping review.Heliyon · 2021Article
- Temporal and spatial analysis of COVID-19 transmission in China and its influencing factors.International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases · 2021Article
- Epidemic Dynamics via Wavelet Theory and Machine Learning with Applications to Covid-19.Biology · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In 2020, Coronavirus Disease 2019 (COVID-19), caused by the SARS-CoV-2 (Severe Acute Respiratory Syndrome Corona Virus 2) Coronavirus, unforeseen pandemic put humanity at big risk and health professionals are facing several kinds of problem due to rapid growth of confirmed cases. That is why some prediction methods are required to estimate the magnitude of infected cases and masses of studies on distinct methods of forecasting are represented so far. In this study, we proposed a hybrid machine learning model that is not only predicted with good accuracy but also takes care of uncertainty of predictions. The model is formulated using Bayesian Ridge Regression hybridized with an n-degree Polynomial and uses probabilistic distribution to estimate the value of the dependent variable instead of using traditional methods. This is a completely mathematical model in which we have successfully incorporated with prior knowledge and posterior distribution enables us to incorporate more upcoming data without storing previous data. Also, L
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.