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We applied a scalable computational framework to extract item\u2010level features from fluency responses in semantic variant (svPPA) and logopenic variant PPA (lvPPA) to test their value for differential diagnosis.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>METHODS<\/jats:title>\n                    <jats:p>We analyzed animal fluency responses from 113 participants (40 svPPA, 40 lvPPA, 33 controls) using an automated pipeline extracting nine psycholinguistic features. Group differences were examined with (co)variance models, classification with logistic regression, and brain\u2013behavior associations via structural magnetic resonance imaging.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>RESULTS<\/jats:title>\n                    <jats:p>All features except semantic variability distinguished svPPA from lvPPA. Models including features outperformed (area under the curve [AUC]\u00a0=\u00a00.86) those using only total correct or clinical variables (AUC\u00a0=\u00a00.60\u20130.68). Features related mainly to temporal lobe atrophy, whereas total correct also related to the angular gyrus.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>DISCUSSION<\/jats:title>\n                    <jats:p>Automated item\u2010level analysis offers a sensitive, scalable method for supporting PPA diagnosis and monitoring.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Highlights<\/jats:title>\n                    <jats:p>\n                      <jats:list list-type=\"bullet\">\n                        <jats:list-item>\n                          <jats:p>Automated item\u2010level features from verbal fluency aid semantic variant primary progressive aphasia (PPA) versus logopenic variant PPA diagnosis.<\/jats:p>\n                        <\/jats:list-item>\n                        <jats:list-item>\n                          <jats:p>Item\u2010level fluency features outperform total correct responses for classification.<\/jats:p>\n                        <\/jats:list-item>\n                        <jats:list-item>\n                          <jats:p>Item\u2010level fluency features map onto syndrome\u2010relevant temporal lobe atrophy.<\/jats:p>\n                        <\/jats:list-item>\n                        <jats:list-item>\n                          <jats:p>A scalable, fully automated pipeline enables integration into clinical practice.<\/jats:p>\n                        <\/jats:list-item>\n                        <jats:list-item>\n                          <jats:p>There is potential to support low\u2010burden, objective monitoring of disease progression in PPA.<\/jats:p>\n                        <\/jats:list-item>\n                      <\/jats:list>\n                    <\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/alz.71124","type":"journal-article","created":{"date-parts":[[2026,1,20]],"date-time":"2026-01-20T03:02:03Z","timestamp":1768878123000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Automated item\u2010level measures of verbal fluency in semantic and logopenic primary progressive aphasia"],"prefix":"10.1002","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1808-8843","authenticated-orcid":false,"given":"Jet M. 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