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10.1177/15533506211018671

http://scihub22266oqcxt.onion/10.1177/15533506211018671
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33960853!ä!33960853

suck abstract from ncbi


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pmid33960853      Surg+Innov 2021 ; 28 (2): 214-219
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  • Thoracic Point-of-Care Ultrasound: A SARS-CoV-2 Data Repository for Future Artificial Intelligence and Machine Learning #MMPMID33960853
  • Mohamed Ali AM; El-Alali E; Weltz AS; Rehrig ST
  • Surg Innov 2021[Apr]; 28 (2): 214-219 PMID33960853show ga
  • Current experience suggests that artificial intelligence (AI) and machine learning (ML) may be useful in the management of hospitalized patients, including those with COVID-19. In light of the challenges faced with diagnostic and prognostic indicators in SARS-CoV-2 infection, our center has developed an international clinical protocol to collect standardized thoracic point of care ultrasound data in these patients for later AI/ML modeling. We surmise that in the future AI/ML may assist in the management of SARS-CoV-2 patients potentially leading to improved outcomes, and to that end, a corpus of curated ultrasound images and linked patient clinical metadata is an invaluable research resource.
  • |*Machine Learning[MESH]
  • |*Point-of-Care Systems[MESH]
  • |Aged[MESH]
  • |Aged, 80 and over[MESH]
  • |Artificial Intelligence[MESH]
  • |Biomedical Engineering[MESH]
  • |COVID-19/*diagnostic imaging[MESH]
  • |Female[MESH]
  • |Humans[MESH]
  • |Lung/diagnostic imaging[MESH]
  • |Male[MESH]
  • |Middle Aged[MESH]
  • |SARS-CoV-2[MESH]


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