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For wider availability of this technology for clinical settings, bias\u2010free quantitative evaluation of tau images without a priori disease information is needed.<\/jats:p><\/jats:sec><jats:sec><jats:title>Objective<\/jats:title><jats:p>We aimed to establish tau PET pathology indices to characterize PSP and AD using a machine learning approach and test their validity and tracer capabilities.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>Data were obtained from 50 healthy control subjects, 46 patients with PSP Richardson syndrome, and 37 patients on the AD continuum. Tau PET data from 114 regions of interest were subjected to Elastic Net cross\u2010validation linear classification analysis with a one\u2010versus\u2010the\u2010rest multiclass strategy to obtain a linear function that discriminates diseases by maximizing the area under the receiver operating characteristic curve. We defined PSP\u2010 and AD\u2010tau scores for each participant as values of the functions optimized for differentiating PSP (4R) and AD (3R\u2009+\u20094R), respectively, from others.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>The discriminatory ability of PSP\u2010 and AD\u2010tau scores assessed as the area under the receiver operating characteristic curve was 0.98 and 1.00, respectively. PSP\u2010tau scores correlated with the PSP rating scale in patients with PSP, and AD\u2010tau scores correlated with Mini\u2010Mental State Examination scores in healthy control\u2013AD continuum patients. The globus pallidus and amygdala were highlighted as regions with high weight coefficients for determining PSP\u2010 and AD\u2010tau scores, respectively.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions<\/jats:title><jats:p>These findings highlight our technology's unbiased capability to identify topologies of 3R\u2009+\u20094R versus 4R tau deposits. \u00a9 2022 The Authors. <jats:italic>Movement Disorders<\/jats:italic> published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society<\/jats:p><\/jats:sec>","DOI":"10.1002\/mds.29173","type":"journal-article","created":{"date-parts":[[2022,8,28]],"date-time":"2022-08-28T12:00:26Z","timestamp":1661688026000},"page":"2236-2246","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":38,"title":["A Machine Learning\u2013Based Approach to Discrimination of Tauopathies Using [<scp><sup>18<\/sup>F<\/scp>]<scp>PM\u2010PBB3 PET<\/scp> 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