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J Digit Imaging ; 36(1): 365-372, 2023 02.
Artigo em Inglês | MEDLINE | ID: mdl-36171520

RESUMO

We describe the curation, annotation methodology, and characteristics of the dataset used in an artificial intelligence challenge for detection and localization of COVID-19 on chest radiographs. The chest radiographs were annotated by an international group of radiologists into four mutually exclusive categories, including "typical," "indeterminate," and "atypical appearance" for COVID-19, or "negative for pneumonia," adapted from previously published guidelines, and bounding boxes were placed on airspace opacities. This dataset and respective annotations are available to researchers for academic and noncommercial use.


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COVID-19 , Humanos , Inteligência Artificial , Radiografia , Aprendizado de Máquina , Radiologistas , Radiografia Torácica/métodos
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