% 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{More:908493,
      author       = {More, Shammi and Antonoupolous, Georgios and Hoffstaedter,
                      Felix and Caspers, Julian and Eickhoff, Simon and Patil,
                      Kaustubh},
      title        = {{B}rain-age prediction: a systematic comparison of machine
                      learning workflows},
      reportid     = {FZJ-2022-02636},
      year         = {2022},
      abstract     = {Prediction of age using anatomical brain MRI, i.e., brain
                      age, is proving valuable in exploring accelerated aging
                      (brain age delta) as a proxy for aging-related diseases and
                      crucial future health outcomes [1]. While various data
                      representations and machine learning (ML) algorithms have
                      been used for brain-age prediction [2,3], the impact of
                      these choices on prediction accuracy remains
                      uncharacterized. Moreover, several methodological challenges
                      remain before a predictive model can be deployed in the real
                      world; (1) robust within-site performance, (2) accurate
                      cross-site prediction and, (3) consistent prediction for the
                      same individual. To fill this gap, we systematically
                      evaluated 70 workflows consisting of ten feature spaces
                      derived from grey matter (GM) images and seven ML algorithms
                      with diverse inductive biases to establish guidelines for
                      designing brain-age prediction workflows.},
      month         = {Jun},
      date          = {2022-06-19},
      organization  = {Organization for Human Brain Mapping,
                       Glasgow (Scotland), 19 Jun 2022 - 23
                       Jun 2022},
      subtyp        = {After Call},
      cin          = {INM-7},
      cid          = {I:(DE-Juel1)INM-7-20090406},
      pnm          = {5251 - Multilevel Brain Organization and Variability
                      (POF4-525) / 5254 - Neuroscientific Data Analytics and AI
                      (POF4-525)},
      pid          = {G:(DE-HGF)POF4-5251 / G:(DE-HGF)POF4-5254},
      typ          = {PUB:(DE-HGF)24},
      url          = {https://juser.fz-juelich.de/record/908493},
}