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@ARTICLE{Shi:979661,
      author       = {Shi, Jianye and Manjunatha, Kiran and Behr, Marek and Vogt,
                      Felix and Reese, Stefanie},
      title        = {{A} physics-informed deep learning framework for modeling
                      of coronary in-stent restenosis},
      journal      = {Biomechanics and modeling in mechanobiology},
      volume       = {23},
      number       = {2},
      issn         = {1617-7959},
      address      = {Berlin ; Heidelberg ; New York, NY},
      publisher    = {Springer},
      reportid     = {RWTH-2024-01739},
      pages        = {615-629},
      year         = {2024},
      note         = {Person Shi, Jianye auch Corresponding author},
      cin          = {311510 / 932110 / 416010},
      ddc          = {540},
      cid          = {$I:(DE-82)311510_20140620$ / $I:(DE-82)531010-2_20140620$ /
                      $I:(DE-82)416010_20140620$},
      pnm          = {DFG project 465213526 - In-Stent-Restenose in koronaren
                      Arterien - In silico-Untersuchungen basierend auf
                      patientenspezifischen Daten und Metamodellierung (465213526)
                      / DFG project 395712048 - Medikamente freisetzende
                      Koronarstents in stenotischen Arterien: medizinische
                      Untersuchung und numerische Modellierung (395712048) / DFG
                      project 403471716 - Experimentelle Untersuchungen und
                      Modellierung von biohybriden Herzklappen inklusive
                      Gewebereifung – von in vitro zu in situ Tissue Engineering
                      (403471716) / DFG project 441884911 - SPP 2311: Robuste
                      Kopplung kontinuumsbiomechanischer in silico Modelle für
                      aktive biologische Systeme als Vorstufe klinischer
                      Applikationen - Co-Design von Modellierung, Numerik und
                      Nutzbarkeit (441884911)},
      pid          = {G:(GEPRIS)465213526 / G:(GEPRIS)395712048 /
                      G:(GEPRIS)403471716 / G:(GEPRIS)441884911},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:001144150200001},
      pubmed       = {pmid:38236483},
      doi          = {10.1007/s10237-023-01796-1},
      url          = {https://publications.rwth-aachen.de/record/979661},
}