% IMPORTANT: The following is UTF-8 encoded.  This means that in the presence
% of non-ASCII characters, it will not work with BibTeX 0.99 or older.
% Instead, you should use an up-to-date BibTeX implementation like “bibtex8” or
% “biber”.

@INPROCEEDINGS{Fonck:1006738,
      author       = {Fonck, Simon and Fritsch, Sebastian and Nottenkämper, Gina
                      and Stollenwerck, Andre},
      title        = {{I}mplementation of {R}es{N}et-50 for the {D}etection of
                      {ARDS} in {C}hest {X}-{R}ays using transfer-learning},
      journal      = {Proceedings on automation in medical engineering},
      volume       = {2},
      number       = {1},
      address      = {Lübeck},
      publisher    = {Infinite Science GmbH},
      reportid     = {FZJ-2023-01817},
      pages        = {ID 742},
      year         = {2023},
      abstract     = {Acute Respiratory Distress Syndrome is a severe condition
                      with high morbidity and mortality. The current standard for
                      the diagnosis of ARDS was proposed by the Berlin-Definition
                      in 2012. However, studies have shown, that ARDS is often
                      recognized too late or not at all. Smart methods, like
                      machine learning algorithms, may help clinicians to identify
                      ARDS earlier and therefore initiate the appropriate therapy.
                      To address the imaging assessment of the Berlin-Definition,
                      a deep learning model for the detection of ARDS in x-rays is
                      proposed. The model achieved an AUCscore of $92.6\%,$ a
                      sensitivity of $87\%$ and a specificity of $97\%.$},
      month         = {Mar},
      date          = {2023-03-30},
      organization  = {16. Interdisziplinäres Symposium
                       Automatisierungstechnische Verfahren
                       für die Medizintechnik, Gießen
                       (Germany), 30 Mar 2023 - 31 Mar 2023},
      cin          = {JSC},
      ddc          = {620},
      cid          = {I:(DE-Juel1)JSC-20090406},
      pnm          = {5112 - Cross-Domain Algorithms, Tools, Methods Labs (ATMLs)
                      and Research Groups (POF4-511) / SMITH -
                      Medizininformatik-Konsortium - Beitrag Forschungszentrum
                      Jülich (01ZZ1803M)},
      pid          = {G:(DE-HGF)POF4-5112 / G:(BMBF)01ZZ1803M},
      typ          = {PUB:(DE-HGF)16 / PUB:(DE-HGF)8},
      url          = {https://juser.fz-juelich.de/record/1006738},
}