% 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”.

@MISC{Knab:169097,
      author       = {Knab, Felix and Koch, Stefan Paul and Major, Sebastian and
                      Farr, Tracy D. and Mueller, Susanne and Euskirchen, Philipp
                      and Eggers, Moritz and Kuffner, Melanie T. C. and Walter,
                      Josefine and Dreier, Jens P. and Endres, Matthias and
                      Dirnagl, Ulrich and Wenger, Nikolaus and Hoffmann, Christian
                      and Boehm-Sturm, Philipp and Harms, Christoph},
      title        = {{D}ataset: {O}pen data repository, {K}nab et al.,
                      {P}rediction of stroke outcome in mice based on non-invasive
                      {MRI} and behavioral testing, v3.1},
      publisher    = {Zenodo},
      reportid     = {DZNE-2022-01804},
      year         = {2022},
      abstract     = {Open data repository, Knab et al., Prediction of stroke
                      outcome in mice based on non-invasive MRI and behavioral
                      testing Latest version of files: $repository_v2.0.zip$ and
                      Behavior $Data_v2.0.xlsx,$ please ignore repository.zip Open
                      data repository Knab et al. Prediction of stroke outcome in
                      mice based on non-invasvive MRI and behavioral testing
                      Content: README.txt This information dat Contains MRI data
                      in NIFTI format and secondary data from atlas registration.
                      For documentation of atlas registration files see
                      https://pubmed.ncbi.nlm.nih.gov/28829217/ Files used for the
                      manuscript: t2.nii: t2 weighted image acquired 24 h post
                      stroke masklesion.nii: manually delineated lesion
                      $x_masklesion.nii:$ lesion in atlas space $ix_ANO.nii:$
                      Allen brain atlas in native space (i.e. matching t2.nii)
                      Lesion volume was calculated by volume of voxels unequal 0
                      in $x_masklesion.nii$ Overlap of regions defined by
                      $ix_ANO.nii$ with masklesion.nii were used for calculating
                      percent damage in each atlas region $prediction_models$
                      Contains separated training and test data as xlsx and csv
                      files with lesion volumes in cubic mm of the Allen brain
                      atlas space, percent damage per atlas region and behavioral
                      data. The training data was used as input for training
                      prediction models in MATLAB, the results were created using
                      the test data. The files have following sturcture: Column 1:
                      animal ID Columns 2-537: MRI regions (column title
                      corresponds to the region number as used in the Allen common
                      coordinate framework) Column 538: lesion volume Column 539:
                      initial performance (subacute deficit) = mean
                      performance/deficit on days 2-6 Column 540: mean
                      performance/deficit on days 2-6 = initial performance
                      (subacute deficit) - this column equals column 539 but has
                      different header which was used to train the residual from
                      initial deficit Column 541: residual performance/deficit
                      Column 542: test or training group Consecutive rows contain
                      data for each animal specified by the animal id The
                      repository also contains all trained models, prediction
                      results for the test data and tables with resulting median
                      absolute error (MedAE) and 5th, 25th, 75th and 95 absolute
                      error quantiles for each model. The model files end with
                      $'_models.mat'$ and contain 50 independently trained models
                      each. Each model version is specified by number 1-50. The
                      result files end with $'_test_results.mat'$ or
                      $'_test_results.xlsx',$ files with MedAE and quantiles end
                      with $'_test_errors.xlsx'$ or $'_test_errors.csv.$ The
                      common part of filenames specifies the used paradigm Folder
                      'subacute deficit prediction' contains: -
                      $initial_performance_from_lesion_volume:$ prediction of
                      subacute deficit using lesion volume -
                      $initial_performance_from_segmented_mri:$ prediction of
                      subacute deficit using segmented mri Folder 'long-term
                      outcome prediction' contains: - $lesion_volume:$ prediction
                      of residual deficit using lesion volume - $segmented_mri:$
                      prediction of residual deficit using $segmented_mri$ -
                      $initial_performance:$ prediction of residual deficit using
                      subacute deficit Folder $'mri_inc_oob_imp'$ contains models
                      trained using increasing number of mri segments sorted
                      according to the out-of-bag importance. The number of used
                      segments is given in the file name. The models, results and
                      errors are separated in subfolders. Files with equal file
                      name and different extension always contain the same data
                      templates Allen atlas, template, brain mask, hemisphere
                      masks, tissue probability masks in NIFTI format including
                      annotations of region IDs and parameter.m file for use in
                      MATLAB toolbox ANTx2},
      keywords     = {stroke (Other) / mice (Other) / outcome prediction (Other)
                      / motor-function (Other) / staircase (Other)},
      cin          = {AG Endres / AG Dirnagl},
      cid          = {I:(DE-2719)1811005 / I:(DE-2719)1810002},
      pnm          = {353 - Clinical and Health Care Research (POF4-353)},
      pid          = {G:(DE-HGF)POF4-353},
      typ          = {PUB:(DE-HGF)32},
      doi          = {10.5281/zenodo.7331723},
      url          = {https://pub.dzne.de/record/169097},
}