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10.1109/MPULS.2020.3008354

http://scihub22266oqcxt.onion/10.1109/MPULS.2020.3008354
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32804639!ä!32804639

suck abstract from ncbi


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pmid32804639      IEEE+Pulse 2020 ; 11 (4): 2-7
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  • AI-Driven COVID-19 Tools to Interpret, Quantify Lung Images #MMPMID32804639
  • Mertz L
  • IEEE Pulse 2020[Jul]; 11 (4): 2-7 PMID32804639show ga
  • Qualitative interpretation is a good thing when it comes to reading lung images in the fight against coronavirus 2019 disease (COVID-19), but quantitative analysis makes radiology reporting much more comprehensive. To that end, several research groups have begun looking to artificial intelligence (AI) as a tool for reading and analyzing X-rays and computed tomography (CT) scans, and helping to diagnose and monitor COVID-19.
  • |*Artificial Intelligence[MESH]
  • |*Radiographic Image Interpretation, Computer-Assisted[MESH]
  • |*Tomography, X-Ray Computed[MESH]
  • |Algorithms[MESH]
  • |Betacoronavirus[MESH]
  • |COVID-19[MESH]
  • |Coronavirus Infections/*diagnostic imaging[MESH]
  • |Humans[MESH]
  • |Lung/*diagnostic imaging[MESH]
  • |Pandemics[MESH]
  • |Pneumonia, Viral/*diagnostic imaging[MESH]


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