@article{ETD,
      recid = {787},
      author = {Tucker Prud'hommeaux, Emily},
      title = {Alignment of narrative retellings for automated  neuropsychological assessment},
      publisher = {Oregon Health and Science University},
      school = {Ph.D.},
      address = {2012},
      number = {ETD},
      abstract = {As neurological disorders such as dementia, autism, and  language impairment become more common, there is growing  need for simple, objective screening tools. Narrative  retelling tasks—where subjects listen to a short story and  retell it—offer promise because these abilities are often  impaired in affected populations. This dissertation  evaluates the reliability and diagnostic utility of  automated narrative analysis. We introduce a novel word  alignment method using random walks, achieving faster and  more accurate alignment than traditional approaches.  Automated scoring based on these alignments predicts  impairment with accuracy comparable to manual scoring and  generalizes to other language samples, supporting its  potential as a flexible screening tool.},
      url = {http://digitalcollections.ohsu.edu/record/787},
      doi = {https://doi.org/10.6083/M4X63JZK},
}