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However, they have not been benchmarked against standard cognitive and neuroimaging measures, missing a critical validation milestone.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>METHODS<\/jats:title>\n                    <jats:p>Thirty\u2010three AD patients and 33 healthy controls completed verbal fluency tasks, episodic memory and executive tests, and magnetic resonance imaging (MRI) (volume) and functional MRI (fMRI) (connectivity) scans. Between\u2010group machine learning classification was compared among fluency\u2010derived DSBs, episodic and executive test scores, MRI, and fMRI measures.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>RESULTS<\/jats:title>\n                    <jats:p>\n                      The fluency classifier's performance (area under the curve [AUC]\u00a0=\u00a00.84) was comparable (\n                      <jats:italic>p<\/jats:italic>\n                      \u00a0&gt;\u00a00.14) to the episodic (AUC\u00a0=\u00a00.90), executive (AUC\u00a0=\u00a00.79), and structural (AUC\u00a0=\u00a00.90) classifiers and superior to the functional classifier (AUC\u00a0=\u00a00.65,\n                      <jats:italic>p<\/jats:italic>\n                      \u00a0=\u00a00.002). Top discriminating features were word length and frequency, both associated with right (pre)frontal volume upon adjusting for sociodemographic factors.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>DISCUSSION<\/jats:title>\n                    <jats:p>DSBs appear non\u2010inferior to standard cognitive and imaging measures, supporting scalable AD assessments in Latinos.<\/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>We examined digital speech biomarkers (DSBs) for detecting AD in Latinos.<\/jats:p>\n                        <\/jats:list-item>\n                        <jats:list-item>\n                          <jats:p>DSBs were benchmarked against cognitive and neuroimaging features.<\/jats:p>\n                        <\/jats:list-item>\n                        <jats:list-item>\n                          <jats:p>DSB\u2010based classifiers matched or outperformed cognitive and brain classifiers.<\/jats:p>\n                        <\/jats:list-item>\n                        <jats:list-item>\n                          <jats:p>Top DSBs included word length, phonological neighborhood, and frequency.<\/jats:p>\n                        <\/jats:list-item>\n                        <jats:list-item>\n                          <jats:p>Word length and frequency correlated with right (pre)frontal brain volume.<\/jats:p>\n                        <\/jats:list-item>\n                      <\/jats:list>\n                    <\/jats:p>\n                  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