ArticleInformatics in medicine unlocked2020
Data analytics for novel coronavirus disease.
Article in Informatics in medicine unlocked, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed.
- Statistical modelling and forecasting of HIV and anti-retroviral therapy cases by time-series and machine learning models.Scientific reports · 2025Article
- Cayley-Purser secured communication and jackknife correlative classification for COVID patient data analysis.Scientific reports · 2025Article
- Variations in Furin SNPs, a Major Concern of SARS-CoV-2 Susceptibility Among Different Populations: AnBioinformatics and biology insights · 2024Article
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- Automated COVID-19 diagnosis and classification using convolutional neural network with fusion based feature extraction model.Cognitive neurodynamics · 2023Article
- An effective deep residual network based class attention layer with bidirectional LSTM for diagnosis and classification of COVID-19.Journal of applied statistics · 2023Article
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- Real-time data of COVID-19 detection with IoT sensor tracking using artificial neural network.Computers & electrical engineering : an international journal · 2022Article
- Improved disease diagnosis system for COVID-19 with data refactoring and handling methods.Frontiers in psychology · 2022Article
- Diagnosis of hypercritical chronic pulmonary disorders using dense convolutional network through chest radiography.Multimedia tools and applications · 2022Article
- An overview of vaccine development for COVID-19.Therapeutic delivery · 2021Review
- Flow Immersive: A Multiuser, Multidimensional, Multiplatform Interactive Covid-19 Data Visualization Tool.Frontiers in psychology · 2021Article
- NSGA-II as feature selection technique and AdaBoost classifier for COVID-19 prediction using patient's symptoms.Nonlinear dynamics · 2021Article
- Diagnosis of breast cancer based on modern mammography using hybrid transfer learning.Multidimensional systems and signal processing · 2021Article
- Article
- SMOTE-NC and gradient boosting imputation based random forest classifier for predicting severity level of covid-19 patients with blood samples.Neural computing & applications · 2021Article
- Hybrid deep learning for detecting lung diseases from X-ray images.Informatics in medicine unlocked · 2020Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This paper describes different aspects of novel coronavirus disease (COVID-19), presents visualization of the spread of the infection, and discusses the potential applications of data analytics on this viral infection. Firstly, a literature survey is done on COVID-19 highlighting a number of factors including its origin, its similarity with previous coronaviruses, its transmission capacity, its symptoms, etc. Secondly, data analytics is applied on a dataset of Johns Hopkins University to find out the spread of the viral infection. It is shown here that although the disease started in China in December 2019, the highest number of confirmed cases up to June 04, 2020 is in the USA. Thirdly, the worldwide increase in the number of confirmed cases over time is modelled here using a polynomial regression algorithm with degree 2. Fourthly, classification algorithms are applied on a dataset of 5644 samples provided by Hospital Israelita Albert Einstein of Brazil in order to diagnose COVID-19. It is shown here that multilayer perceptron (MLP), XGBoost and logistic regression can classify COVID-19 patients at an accuracy above 91%. Finally, a discussion is presented on the potential applications of data analytics in several important factors of COVID-19.
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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.