A Promising and Challenging Approach: Radiologists' Perspective on Deep Learning and Artificial Intelligence for Fighting COVID-19

Tianming Wang; Zhu Chen; Quanliang Shang; Cong Ma; Xiangyu Chen; Enhua Xiao

doi:10.3390/diagnostics11101924

A Promising and Challenging Approach: Radiologists' Perspective on Deep Learning and Artificial Intelligence for Fighting COVID-19

Diagnostics (Basel). 2021 Oct 18;11(10):1924. doi: 10.3390/diagnostics11101924.

Authors

Tianming Wang^{1

2}, Zhu Chen¹, Quanliang Shang¹, Cong Ma¹, Xiangyu Chen¹, Enhua Xiao^{1

3}

Affiliations

¹ Department of Radiology, The Second Xiangya Hospital, Central South University, Changsha 410011, China.
² Department of Radiology, Xiangya Hospital, Central South University, Changsha 410008, China.
³ Molecular Imaging Research Center, Central South University, Changsha 410008, China.

Abstract

Chest X-rays (CXR) and computed tomography (CT) are the main medical imaging modalities used against the increased worldwide spread of the 2019 coronavirus disease (COVID-19) epidemic. Machine learning (ML) and artificial intelligence (AI) technology, based on medical imaging fully extracting and utilizing the hidden information in massive medical imaging data, have been used in COVID-19 research of disease diagnosis and classification, treatment decision-making, efficacy evaluation, and prognosis prediction. This review article describes the extensive research of medical image-based ML and AI methods in preventing and controlling COVID-19, and summarizes their characteristics, differences, and significance in terms of application direction, image collection, and algorithm improvement, from the perspective of radiologists. The limitations and challenges faced by these systems and technologies, such as generalization and robustness, are discussed to indicate future research directions.

Keywords: COVID-19; artificial intelligence; deep learning; machine learning; medical imaging.

Publication types

Review