ArticleDiabetes & metabolic syndrome
Prediction of new active cases of coronavirus disease (COVID-19) pandemic using multiple linear regression model.
Article in Diabetes & metabolic syndrome. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers.
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Who cites it
40 citing papers in PubMed.
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- Evaluation of serum and urine biomarkers for severe COVID-19.Frontiers in medicine · 2024Article
- Prediction of cross-border spread of the COVID-19 pandemic: A predictive model for imported cases outside China.PloS one · 2024Article
- Deep learning based hybrid prediction model for predicting the spread of COVID-19 in the world's most populous countries.Expert systems with applications · 2023Article
- The relationship between PMHeliyon · 2023Article
- Cluster analysis and forecasting of viruses incidence growth curves: Application to SARS-CoV-2.Expert systems with applications · 2023Article
- Prediction of COVID-19 Using a WOA-BILSTM Model.Bioengineering (Basel, Switzerland) · 2023Article
- A new hybrid prediction model of COVID-19 daily new case data.Engineering applications of artificial intelligence · 2023Article
- COVID-19 Prediction Using Black-Box Based Pearson Correlation Approach.Diagnostics (Basel, Switzerland) · 2023Article
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- Application of big data and artificial intelligence in epidemic surveillance and containment.Intelligent medicine · 2023Review
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- Ambient air pollutants concentration prediction during the COVID-19: A method based on transfer learning.Knowledge-based systems · 2022Article
- Prediction of global omicron pandemic using ARIMA, MLR, and Prophet models.Scientific reports · 2022Article
- A deep spatio-temporal meta-learning model for urban traffic revitalization index prediction in the COVID-19 pandemic.Advanced engineering informatics · 2022Article
- A novel reliability-based regression model to analyze and forecast the severity of COVID-19 patients.BMC medical informatics and decision making · 2022Article
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3 authors.
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No grant is acknowledged in the PubMed record.
Abstract
INTRODUCTION AND
aimsThe COVID-19 pandemic originated from the city of Wuhan of China has highly affected the health, socio-economic and financial matters of the different countries of the world. India is one of the countries which is affected by the disease and thousands of people on daily basis are getting infected. In this paper, an analysis of daily statistics of people affected by the disease are taken into account to predict the next days trend in the active cases in Odisha as well as India. MATERIAL AND
methodsA valid global data set is collected from the WHO daily statistics and correlation among the total confirmed, active, deceased, positive cases are stated in this paper. Regression model such as Linear and Multiple Linear Regression techniques are applied to the data set to visualize the trend of the affected cases.
resultsHere a comparison of Linear Regression and Multiple Linear Regression model is performed where the score of the model R
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