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

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.

Application of artificial intelligence in diagnosing COVID-19 disease symptoms on chest X-rays: A systematic review

“…Nevertheless, the overall number of high-quality studies is negligible, and a lack of prospective studies and external verification is the greatest disadvantage. Most authors obtained data from various collections or institutions to ensure an adequate number of CXRs showing COVID-19, other pathological conditions and pathology-free images [44,45], often based only on their own data to a certain extent. Some authors made the datasets they created publicly available [38].…”

“…Then, many diverse information technology (IT) ideas were proposed, such as transfer learning techniques or novel network architectures, to improve CXR diagnostic performance in COVID-19 disease. In the initial period of the pandemic, an insufficient amount of image data limited the development of research on AI in COVID-19 diagnostics because there were no sufficiently large databases that could be used in scientific research [24,25]. Currently, we have large, publicly available datasets that contain CXR from patients with active SARS-CoV-2 infection [26 -28].…”

Empowering Healthcare with Machine Learning: A Comprehensive Review of Machine Learning-based COVID-19 Detection, Diagnosis and Treatment

“…Though ML has shown potential in COVID-19 diagnosis and therapy, further study is needed to improve the robustness and reliability of COVID-19 diagnostic and treatment ML systems. [13][14][15][16][17]…”

Deep learning‐based COVID‐19 diagnosis using CT scans with laboratory and physiological parameters

“…The medical field has already leveraged artificial neural network (ANN) techniques with machine learning and deep learning algorithms to assist radiologists in detecting and diagnosing SARS-CoV2 based on lung CT imaging techniques [19][20][21][22][23][24]. Specifically, convolutional neural network (CNN)based deep learning algorithms are preferred to address imaging classification for COVID-19 diagnosis [25] due to the specialized feature extraction capabilities for digital images.…”