7 Data Science Research Papers on Covid-19- You Should Read

During the Covid-19 Pandemic, lots of researchers are giving their contributions and published research papers. That’s why I thought to share some Data Science Research Papers on Covid-19 with you. These research papers are on various topics such as patient monitoring using deep learning or predict the country-wise Covid-19 using neural networks.

So without any further ado, let’s get started-

Data Science Research Papers on Covid-19

1. Coronavirus (COVID-19) Classification using CT Images by Machine Learning Methods

Authors- Mucahid Barstugan, Umut Ozkaya, Saban Ozturk

In this research paper, the authors present early phase detection of Coronavirus (COVID-19) by using machine learning methods. They implement the detection process on abdominal Computed Tomography (CT) images. For classification, they applied Support Vector Machines (SVM). And for evaluation of the model performance, they use Sensitivity, specificity, accuracy, precision, and F-score metrics.

For more details- Read Paper

2. Large-Scale Screening of COVID-19 from Community-Acquired Pneumonia using Infection Size-Aware Classification

Authors- Feng Shi, Liming Xia, Fei Shan, Dijia Wu, Ying Wei, Huan Yuan, Huiting Jiang, Yaozong Gao, He Sui, Dinggang Shen

In this research paper, the authors developed a method for screening Covid-19 on a large scale by using the Infection Size Aware Random Forest method (iSARF). They collected CT images of a total of 2685, where 1658 cases were the confirmed COVID-19 cases and 1027 cases were CAP patients.

For more details- Read Paper

Related Article- 10 Best Online Courses for Data Science with R Programming in 2025

3. Neural network-based country-wise risk prediction of COVID-19

Authors- Ratnabali Pal, Arif Ahmed Sekh, Samarjit Kar, Dilip K. Prasad

In this paper, the researchers propose a shallow long short-term memory (LSTM) based neural network to predict the risk category of a country. For optimization and automatically design country-specific networks they used the Bayesian optimization framework. They have also experimented with the trend data and weather data combined for the prediction.

For more details– Read Paper

4. Neural Network aided quarantine control model estimation of COVID spread in Wuhan, China

Authors- Raj Dandekar, George Barbastathis

The researcher’s results indicate that the strict public health policies implemented in Wuhan may have played a crucial role in halting down the spread of infection and such measures should potentially be implemented in other highly affected countries. They used two models- Without quarantine control and With quarantine control.

For more details– Read Paper

5. Rapid AI Development Cycle for the Coronavirus (COVID-19) Pandemic: Initial Results for Automated Detection & Patient Monitoring using Deep Learning CT Image Analysis

Authors- Ophir Gozes, Maayan Frid-Adar, Hayit Greenspan, Patrick D. Browning, Huangqi Zhang, Wenbin Ji, Adam Bernheim, Eliot Siegel

The purpose of the researchers was to develop AI-based automated CT image analysis tools for detection, quantification, and tracking of Coronavirus and demonstrate that they can differentiate coronavirus patients from those who do not have the disease. For this work, they use Multiple international datasets.

For more details- Read Paper

6. Leveraging Data Science to Combat COVID-19: A Comprehensive Review

Authors- Siddique Latif , Muhammad Usman , Sanaullah Manzoor, Junaid Qadir, Adeel Razi, Maged N. Kamel Boulos, and Jon Crowcroft

This is a review paper where researchers attempt to systematize the various COVID-19 research activities leveraging data science, where they define data science broadly to encompass the various methods and tools—including those from artificial intelligence, machine learning, statistics, modeling, simulation, and data visualization. This research paper is mainly intended for a computer science and engineering audience.

For more details- Read Paper

7. COVID-Net: A Tailored Deep Convolutional Neural Network Design for Detection of COVID-19 Cases from Chest X-Ray Images

Authors- Linda Wang, Alexander Wong

In this research paper, the researchers introduced COVID-Net, a deep convolutional neural network design tailored for the detection of COVID-19 cases from chest X-ray (CXR) images that is open source and available to the general public. For this work, they combined and modified five different publicly available data repositories- COVID-19 Image Data Collection, COVID-19 Chest X-ray Dataset, ActualMed COVID-19 Chest X-ray Dataset, RSNA Pneumonia Detection Challenge dataset, and COVID-19 radiography database.

For more details- Read Paper

So these are 7 Data Science Research Papers on Covid-19. Now it’s time to wrap up.

Conclusion

I hope you will find these Data Science Research Papers on Covid-19 helpful. If you have any doubt or questions, feel free to ask me in the comment section.

All the Best!

Enjoy Learning!

Thank YOU!

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