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    <identifier>10.57760/sciencedb.21601</identifier>
    <datestamp>2025-03-13T09:48:39Z</datestamp>
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  <dc:date>2025-03-13</dc:date>
  <dc:title>COVID-CT-DS</dc:title>
  <dc:identifier>doi:10.57760/sciencedb.21601</dc:identifier>
  <dc:language>en</dc:language>
  <dc:description>COVID-CT-DS is a comprehensive dataset designed to advance AI research in medical image analysis for COVID-19. It comprises 278 patient-specific CT cases with varying disease severity (normal: 10, mild: 88, moderate: 112, severe: 48, and fibrosis:16). Each patient-specific HRCT case comprises an average of 550 axial CT images. For each case, a diagnostic report with detailed information is also provided. By providing a large-scale, well-balanced resource, this dataset aims to facilitate the development of AI models capable of accurately assessing disease severity and aiding clinical decision-making.</dc:description>
  <dc:subject>CT images; Medical Imaging; COVID-19; CAD; medical image analysis; dataset</dc:subject>
  <dc:creator>Amruta Ruikar</dc:creator>
  <dc:creator>Amol Vibhute</dc:creator>
  <dc:creator>Dr Darshan Ruikar</dc:creator>
  <dc:rights>PUBLIC</dc:rights>
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  <dc:type>dataset</dc:type>
  <dc:publisher>Science Data Bank</dc:publisher>
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