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        <identifier>oai:b2share.fz-juelich.de:b2rec/aef5d3b8aa044485b9620b95b60c47a2</identifier>
        <datestamp>2021-05-25T22:39:33Z</datestamp>
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          <titles>
            <title>EHL Dataset EOSC Fast Track Grant Covid-19 Data Analysis with CXR Images (Covid-19, Normal, Pneumonia)</title>
          </titles>
          <community>EUDAT</community>
          <identifiers>
            <identifier identifierType="URL">https://b2share.fz-juelich.de/records/aef5d3b8aa044485b9620b95b60c47a2</identifier>
            <identifier identifierType="DOI">10.34730/aef5d3b8aa044485b9620b95b60c47a2</identifier>
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          <publishers>
            <publisher>EUDAT B2SHARE</publisher>
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          <publicationYear>2021</publicationYear>
          <creators>
            <creator>E*HealthLine Inc.</creator>
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          <descriptions>
            <description>The total size of the EHL Data is 305 MB, and the images’ resolutions vary quite a lot. Some Covid-19 images are about 1239x1024 and other normal images in the dataset are mostly around 390x320. The files are 2200 images provided by EHL with labels of Normal, Covid-19, and Pneumonia. The files are separated as train and test datasets used for machine and deep learning analysis.

Dataset Label Train Test Total
EHL Covid-19 84 100 184
EHL Normal 198 1700 1898
EHL Pneumonia 21 97 118</description>
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          <disciplines>
            <discipline>5.13.4 → Medicine → Health informatics</discipline>
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          <keywords>
            <keyword>Covid-19, Covid-Net, Pneumonia, Machine Learning, Deep Learning</keyword>
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            <contact>m.riedel@fz-juelich.de</contact>
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            <size>212.9 MB</size>
            <size>1 file</size>
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