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@ARTICLE{Polzin:1014774,
      author       = {Polzin, Richard and Fritsch, Sebastian and Sharafutdinov,
                      Konstantin and Marx, Gernot and Schuppert, Andreas},
      title        = {{D}iagnostic {E}xpert {A}dvisor: {A} platform for
                      developing machine learning models on medical time-series
                      data},
      journal      = {SoftwareX},
      volume       = {23},
      issn         = {2352-7110},
      address      = {Amsterdam [u.a.]},
      publisher    = {Elsevier},
      reportid     = {FZJ-2023-03458},
      pages        = {101517},
      year         = {2023},
      abstract     = {Setting up data structures, parallelizing code, and
                      creating visualizations are tasks in almost any project
                      aiming to develop healthcare AI solutions based on
                      heterogeneous, high-dimensional data structures. While
                      toolkits for individual parts of this workflow exist, a
                      solution that provides integration of all steps is rarely
                      found. We present the Diagnostic Expert Advisor, a platform
                      for machine learning research on heterogeneous medical
                      time-series data that aims to provide a robust environment
                      for the rapid development of AI applications. It integrates
                      a local web app through which whole patient cohorts, as well
                      as the disease evolution of individual patients, can be
                      analyzed with integrated tools for data handling,
                      visualization, and parallelization. The platform provides
                      sensible defaults while being flexible and extensible to fit
                      various projects and working styles.},
      cin          = {JSC},
      ddc          = {004},
      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) / BMBF 01ZZ1803B - SMITH -
                      Medizininformatik-Konsortium - Beitrag Universitätsklinikum
                      Aachen (01ZZ1803B)},
      pid          = {G:(DE-HGF)POF4-5112 / G:(BMBF)01ZZ1803M /
                      G:(BMBF)01ZZ1803B},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:001075618700001},
      doi          = {10.1016/j.softx.2023.101517},
      url          = {https://juser.fz-juelich.de/record/1014774},
}