{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T10:59:52Z","timestamp":1785581992077,"version":"3.56.0"},"reference-count":48,"publisher":"Wiley","issue":"2","license":[{"start":{"date-parts":[[2026,4,15]],"date-time":"2026-04-15T00:00:00Z","timestamp":1776211200000},"content-version":"vor","delay-in-days":14,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"},{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"funder":[{"DOI":"10.13039\/100014808","name":"Fondation Vaincre Alzheimer","doi-asserted-by":"publisher","award":["70202"],"award-info":[{"award-number":["70202"]}],"id":[{"id":"10.13039\/100014808","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["alz-journals.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Alz &amp;amp; Dem Diag Ass &amp;amp; Dis Mo"],"published-print":{"date-parts":[[2026,4]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>INTRODUCTION<\/jats:title>\n                    <jats:p>Affective disturbances are common across behavioral variant frontotemporal degeneration (bvFTD), primary psychiatric disorders (PPD), and Alzheimer's disease (AD). Objective markers are needed for differential and transdiagnostic characterization. We tested whether artificial intelligence (AI)\u2010based analysis of natural speech could provide such markers.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>METHODS<\/jats:title>\n                    <jats:p>Speech from 112 participants (bvFTD\u00a0=\u00a031, AD\u00a0=\u00a028, PPD\u00a0=\u00a015, controls\u00a0=\u00a039) was analyzed using a fine\u2010tuned speech emotion recognition model estimating valence, arousal, dominance, and entropy. Group differences were assessed with analyses of covariance, diagnostic utility with logistic regression, and neuroanatomical correlates with voxel\u2010based morphometry.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>RESULTS<\/jats:title>\n                    <jats:p>Group\u2010specific affective profiles emerged. Overall, PPD exhibited a lower valence. bvFTD and AD showed a reduced arousal and a higher dominance. Affective dimensions predicted bvFTD with 80.4% accuracy (area under the curve\u00a0\u00a0=\u00a0\u00a00.732) and mapped onto fronto\u2010insular and temporal networks. Entropy was identified as a transdiagnostic marker.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>DISCUSSION<\/jats:title>\n                    <jats:p>AI\u2010based speech analysis provides objective, scalable biomarkers for differential diagnosis, transdiagnostic characterization, and disease monitoring.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/dad2.70300","type":"journal-article","created":{"date-parts":[[2026,4,16]],"date-time":"2026-04-16T04:02:26Z","timestamp":1776312146000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["AI\u2010powered analysis of affective dimensions in speech and its relevance for FTD diagnosis"],"prefix":"10.1002","volume":"18","author":[{"ORCID":"https:\/\/orcid.org\/0009-0003-9125-2763","authenticated-orcid":false,"given":"Agn\u00e8s","family":"Den\u00e8ve","sequence":"first","affiliation":[{"name":"Lille Neuroscience &amp; Cognition, Inserm U1172, Univ Lille CHU  Lille France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rosalie","family":"Dauchez","sequence":"additional","affiliation":[{"name":"Lille Neuroscience &amp; Cognition, Inserm U1172, Univ Lille CHU  Lille France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4386-6045","authenticated-orcid":false,"given":"Thibaud","family":"Lebouvier","sequence":"additional","affiliation":[{"name":"Lille Neuroscience &amp; Cognition, Inserm U1172, Univ Lille CHU  Lille France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5683-0490","authenticated-orcid":false,"given":"Fabien","family":"D'Hondt","sequence":"additional","affiliation":[{"name":"Lille Neuroscience &amp; Cognition, Inserm U1172, Univ Lille CHU  Lille France"},{"name":"Centre national de ressources et de r\u00e9silience (Cn2r)  Lille Paris France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5283-503X","authenticated-orcid":false,"given":"Maxime","family":"Bertoux","sequence":"additional","affiliation":[{"name":"Lille Neuroscience &amp; Cognition, Inserm U1172, Univ Lille CHU  Lille France"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2026,4,15]]},"reference":[{"key":"e_1_2_9_2_1","doi-asserted-by":"publisher","DOI":"10.4088\/JCP.10m06382oli"},{"key":"e_1_2_9_3_1","doi-asserted-by":"publisher","DOI":"10.1186\/s13195\u2010020\u201000753\u20109"},{"key":"e_1_2_9_4_1","doi-asserted-by":"publisher","DOI":"10.1176\/appi.neuropsych.20240238"},{"key":"e_1_2_9_5_1","doi-asserted-by":"publisher","DOI":"10.1136\/jnnp\u20102011\u2010301849"},{"key":"e_1_2_9_6_1","doi-asserted-by":"publisher","DOI":"10.1080\/17470919.2011.620779"},{"key":"e_1_2_9_7_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neubiorev.2017.11.014"},{"key":"e_1_2_9_8_1","doi-asserted-by":"publisher","DOI":"10.1093\/brain\/awac382"},{"key":"e_1_2_9_9_1","doi-asserted-by":"publisher","DOI":"10.1002\/trc2.12218"},{"key":"e_1_2_9_10_1","doi-asserted-by":"publisher","DOI":"10.1093\/brain\/awz204"},{"key":"e_1_2_9_11_1","doi-asserted-by":"publisher","DOI":"10.1212\/WNL.0000000000207516"},{"key":"e_1_2_9_12_1","doi-asserted-by":"publisher","DOI":"10.1212\/wnl.0000000000004236"},{"key":"e_1_2_9_13_1","doi-asserted-by":"publisher","DOI":"10.1037\/neu0001041"},{"key":"e_1_2_9_14_1","doi-asserted-by":"publisher","DOI":"10.1002\/dad2.12276"},{"key":"e_1_2_9_15_1","doi-asserted-by":"publisher","DOI":"10.1212\/WNL.0000000000200750"},{"key":"e_1_2_9_16_1","doi-asserted-by":"publisher","DOI":"10.1212\/WNL.0000000000213556"},{"key":"e_1_2_9_17_1","doi-asserted-by":"publisher","DOI":"10.1109\/JSTSP.2022.3207050"},{"key":"e_1_2_9_18_1","doi-asserted-by":"publisher","DOI":"10.1037\/h0077714"},{"key":"e_1_2_9_19_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.biopsycho.2020.107974"},{"key":"e_1_2_9_20_1","doi-asserted-by":"publisher","DOI":"10.1002\/dad2.12594"},{"key":"e_1_2_9_21_1","doi-asserted-by":"publisher","DOI":"10.1093\/brain\/awr179"},{"key":"e_1_2_9_22_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jalz.2011.03.005"},{"key":"e_1_2_9_23_1","doi-asserted-by":"publisher","DOI":"10.1176\/appi.books.9780890425596"},{"key":"e_1_2_9_24_1","volume-title":"Gr\u00e9mots: Evaluation du langage dans les pathologies neurod\u00e9g\u00e9n\u00e9ratives\u2014Catherine B\u00e9zy, Antoine Renard, J\u00e9r\u00e9mie Pariente","author":"B\u00e9zy C","year":"2016"},{"key":"e_1_2_9_25_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2023.3263585"},{"key":"e_1_2_9_26_1","doi-asserted-by":"publisher","DOI":"10.1037\/a0025827"},{"key":"e_1_2_9_27_1","unstructured":"ConneauAC.Reconnaissance automatique de l\u2019\u00e9motion \u00e0 partir de signaux EEG.PhD thesis.T\u00e9l\u00e9com ParisTech.2016. 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