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 2024
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!
You May Also Interested In
Udacity Data Engineering Nanodegree Review in 2024- Should You Enroll?
Is Udacity Data Science Nanodegree Worth It in 2024?
Is DataCamp Good for Learning Data Science or not in 2024?
15 Best Online Courses for Data Science for Everyone in 2024
Data Analyst Online Certification to Become a Successful Data Analyst
8 Best Data Engineering Courses Online- Complete List of Resources
Best Course on Statistics for Data Science to Master in Statistics
8 Best Tableau Courses Online- Find the Best One For You!
8 Best Online Courses on Big Data Analytics You Need to Know
Best SQL Online Course Certificate Programs for Data Science
7 Best SAS Certification Online Courses You Need to Know
Thank YOU!
Explore More about Data Science, Visit Here
Subscribe For More Updates!
[mc4wp_form id=”28437″]
Though of the Day…
‘ It’s what you learn after you know it all that counts.’
– John Wooden
Written By Aqsa Zafar
Founder of MLTUT, Machine Learning Ph.D. scholar at Dayananda Sagar University. Research on social media depression detection. Create tutorials on ML and data science for diverse applications. Passionate about sharing knowledge through website and social media.