# Machine learning applications for COVID-19: A state-of-the-art review

arXiv: https://arxiv.org/abs/2101.07824 · HTML: https://mlsanity.com/paper/2101.07824/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 11 of its 48 references that are in the map.
- First posted on arXiv 19 Jan 2021.

## Builds on (most cited first, 11 of 11)

- [Covid-19: Automatic detection from X-Ray images utilizing Transfer Learning with Convolutional Neural Networks](https://mlsanity.com/paper/2003.11617/) (2020)
- [Automatic Detection of Coronavirus Disease (COVID-19) Using X-ray Images and Deep Convolutional Neural Networks](https://mlsanity.com/paper/2003.10849/) (2020)
- [Examining COVID-19 Forecasting using Spatio-Temporal Graph Neural Networks](https://mlsanity.com/paper/2007.03113/) (2020)
- [Review of Artificial Intelligence Techniques in Imaging Data Acquisition, Segmentation and Diagnosis for COVID-19](https://mlsanity.com/paper/2004.02731/) (2020)
- [Automatic Detection of Coronavirus Disease (COVID-19) in X-ray and CT Images: A Machine Learning-Based Approach](https://mlsanity.com/paper/2004.10641/) (2020)
- [Adaptive Feature Selection Guided Deep Forest for COVID-19 Classification with Chest CT](https://mlsanity.com/paper/2005.03264/) (2020)
- [A Survey of COVID-19 Contact Tracing Apps](https://mlsanity.com/paper/2006.10306/) (2020)
- [Forecasting Brazilian and American COVID-19 cases based on artificial intelligence coupled with climatic exogenous variables](https://mlsanity.com/paper/2007.10981/) (2020)
- [Forecasting significant stock price changes using neural networks](https://mlsanity.com/paper/1912.08791/) (2019)
- [Proximity Sensing: Modeling and Understanding Noisy RSSI-BLE Signals and Other Mobile Sensor Data for Digital Contact Tracing](https://mlsanity.com/paper/2009.04991/) (2020)
- [A Smartphone enabled Approach to Manage COVID-19 Lockdown and Economic Crisis](https://mlsanity.com/paper/2004.12240/) (2020)

## Built on by (most cited first, 2 of 2)

- [COVID-19 Modeling: A Review](https://mlsanity.com/paper/2104.12556/) (2021)
- [Review of Natural Language Processing in Pharmacology](https://mlsanity.com/paper/2208.10228/) (2022)

## Abstract (arXiv)

The COVID-19 pandemic has galvanized the machine learning community to create new solutions that can help in the fight against the virus. The body of literature related to applications of machine learning and artificial intelligence to COVID-19 is constantly growing. The goal of this article is to present the latest advances in machine learning research applied to COVID-19. We cover four major areas of research: forecasting, medical diagnostics, drug development, and contact tracing. We review and analyze the most successful state of the art studies. In contrast to other existing surveys on the subject, our article presents a high level overview of the current research that is sufficiently detailed to provide an informed insight.