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@ARTICLE{Barron:906465,
      author       = {Barron, Daniel S. and Baker, Justin T. and Budde, Kristin
                      S. and Bzdok, Danilo and Eickhoff, Simon B. and Friston,
                      Karl J. and Fox, Peter T. and Geha, Paul and Heisig, Stephen
                      and Holmes, Avram and Onnela, Jukka-Pekka and Powers, Albert
                      and Silbersweig, David and Krystal, John H.},
      title        = {{D}ecision {M}odels and {T}echnology {C}an {H}elp
                      {P}sychiatry {D}evelop {B}iomarkers},
      journal      = {Frontiers in psychiatry},
      volume       = {12},
      issn         = {1664-0640},
      address      = {Lausanne},
      publisher    = {Frontiers Research Foundation},
      reportid     = {FZJ-2022-01468},
      pages        = {706655},
      year         = {2021},
      abstract     = {Why is psychiatry unable to define clinically useful
                      biomarkers? We explore this question from the vantage of
                      data and decision science and consider biomarkers as a form
                      of phenotypic data that resolves a well-defined clinical
                      decision. We introduce a framework that systematizes
                      different forms of phenotypic data and further introduce the
                      concept of decision model to describe the strategies a
                      clinician uses to seek out, combine, and act on clinical
                      data. Though many medical specialties rely on quantitative
                      clinical data and operationalized decision models, we
                      observe that, in psychiatry, clinical data are gathered and
                      used in idiosyncratic decision models that exist solely in
                      the clinician's mind and therefore are outside empirical
                      evaluation. This, we argue, is a fundamental reason why
                      psychiatry is unable to define clinically useful biomarkers:
                      because psychiatry does not currently quantify clinical
                      data, decision models cannot be operationalized and, in the
                      absence of an operationalized decision model, it is
                      impossible to define how a biomarker might be of use. Here,
                      psychiatry might benefit from digital technologies that have
                      recently emerged specifically to quantify clinically
                      relevant facets of human behavior. We propose that digital
                      tools might help psychiatry in two ways: first, by
                      quantifying data already present in the standard clinical
                      interaction and by allowing decision models to be
                      operationalized and evaluated; second, by testing whether
                      new forms of data might have value within an operationalized
                      decision model. We reference successes from other medical
                      specialties to illustrate how quantitative data and
                      operationalized decision models improve patient care.},
      cin          = {INM-7},
      ddc          = {610},
      cid          = {I:(DE-Juel1)INM-7-20090406},
      pnm          = {5252 - Brain Dysfunction and Plasticity (POF4-525)},
      pid          = {G:(DE-HGF)POF4-5252},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:34566711},
      UT           = {WOS:000698452200001},
      doi          = {10.3389/fpsyt.2021.706655},
      url          = {https://juser.fz-juelich.de/record/906465},
}