Deep Learning and Medical Image Analysis for COVID-19 Diagnosis and Prediction.
Annu Rev Biomed Eng
; 24: 179-201, 2022 06 06.
Article
em En
| MEDLINE
| ID: mdl-35316609
The coronavirus disease 2019 (COVID-19) pandemic has imposed dramatic challenges to health-care organizations worldwide. To combat the global crisis, the use of thoracic imaging has played a major role in the diagnosis, prediction, and management of COVID-19 patients with moderate to severe symptoms or with evidence of worsening respiratory status. In response, the medical image analysis community acted quickly to develop and disseminate deep learning models and tools to meet the urgent need of managing and interpreting large amounts of COVID-19 imaging data. This review aims to not only summarize existing deep learning and medical image analysis methods but also offer in-depth discussions and recommendations for future investigations. We believe that the wide availability of high-quality, curated, and benchmarked COVID-19 imaging data sets offers the great promise of a transformative test bed to develop, validate, and disseminate novel deep learning methods in the frontiers of data science and artificial intelligence.
Palavras-chave
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Aprendizado Profundo
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COVID-19
Tipo de estudo:
Diagnostic_studies
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Guideline
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Prognostic_studies
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Qualitative_research
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Risk_factors_studies
Limite:
Humans
Idioma:
En
Ano de publicação:
2022
Tipo de documento:
Article