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A cikk állandó MOB linkje:
http://mob.gyemszi.hu/detailsperm.jsp?PERMID=164009
MOB:2024/2
Szerzők:Nardocci, Chiara; Simon Judit; Budai Bettina Katalin
Tárgyszavak:SOFTWARE; EGÉSZSÉGÜGYI INFORMATIKA ALKALMAZÁSI TERÜLETEI; TOMOGRAPHIA, COMPUTERES, RÖNTGEN-; SARS-COV-2; DIAGNÓZIS; PNEUMONIA
Folyóirat:Imaging - 2024. 16. évf. 1. sz.
[https://akjournals.com/view/journals/1647/1647-overview.xml ]


  Artificial intelligence-based quantification of COVID-19 pneumonia burden using chest CT / Chiara Nardocci, Judit Simon, Bettina Katalin Budai
  Bibliogr.: p. 17-21. - Abstr. eng. - DOI: https://doi.org/10.1556/1647.2024.00167
  In: Imaging. - ISSN eISSN 2732-0960. - 2024. 16. évf. 1. sz., p. 1-21. : ill.


During the coronavirus disease 2019 (COVID-19) pandemic, artificial intelligence (AI) based software on chest computed tomography (CT) imaging has proven to have a valuable role in accelerating diagnosis and screening. The proposed AI-based tools proved to be rapid and reproducible techniques to guide patient management and treatment protocols. Although no specific guidelines exist, CT-imaging and clinical features are used for patient staging. To shed light on the role of AI techniques that have been developed in fighting COVID-19, in this review, studies investigating the usage of commonly used AI models on chest CT imaging for disease quantification and prognostication are collected.  Kulcsszavak: artificial intelligence, neural networks, deep learning, COVID-19, pneumonia, chest CT