On the role of artificial intelligence in medical imaging of COVID-19
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Author / Producer
Date
2021-06-11
Publication Type
Review Article
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yes
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Abstract
Although a plethora of research articles on AI methods on COVID-19 medical imaging are published, their clinical value remains unclear. We conducted the largest systematic review of the literature addressing the utility of AI in imaging for COVID-19 patient care. By keyword searches on PubMed and preprint servers throughout 2020, we identified 463 manuscripts and performed a systematic meta-analysis to assess their technical merit and clinical relevance. Our analysis evidences a significant disparity between clinical and AI communities, in the focus on both imaging modalities (AI experts neglected CT and ultrasound, favoring X-ray) and performed tasks (71.9% of AI papers centered on diagnosis). The vast majority of manuscripts were found to be deficient regarding potential use in clinical practice, but 2.7% (n = 12) publications were assigned a high maturity level and are summarized in greater detail. We provide an itemized discussion of the challenges in developing clinically relevant AI solutions with recommendations and remedies.
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published
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Journal / series
Volume
2 (6)
Pages / Article No.
100269
Publisher
Elsevier
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Edition / version
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Software
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Date collected
Date created
Subject
artificial intelligence; meta-review; COVID-19; Coronavirus; Chest X-Ray; Chest CT; chest ultrasound; machine learning; deep learning; PRISMA; SARS-CoV-2; medical imaging; digital healthcare; lung imaging