{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,30]],"date-time":"2026-07-30T14:13:39Z","timestamp":1785420819807,"version":"3.56.0"},"reference-count":41,"publisher":"SAGE Publications","issue":"2","license":[{"start":{"date-parts":[[2024,12,17]],"date-time":"2024-12-17T00:00:00Z","timestamp":1734393600000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100004337","name":"F. Hoffmann-La Roche Ltd","doi-asserted-by":"crossref","award":["Integrative Neuroscience Collaborations Network"],"award-info":[{"award-number":["Integrative Neuroscience Collaborations Network"]}],"id":[{"id":"10.13039\/100004337","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/100000890","name":"National Multiple Sclerosis Society","doi-asserted-by":"publisher","award":["FAN-2107-38077"],"award-info":[{"award-number":["FAN-2107-38077"]}],"id":[{"id":"10.13039\/100000890","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Mult Scler"],"published-print":{"date-parts":[[2025,2]]},"abstract":"<jats:sec>\n                    <jats:title>Background:<\/jats:title>\n                    <jats:p>Fatigue is a major \u201cinvisible\u201d symptom in people with multiple sclerosis (PwMS), which may affect speech. Automated speech analysis is an objective, rapid tool to capture digital speech biomarkers linked to functional outcomes.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Objective:<\/jats:title>\n                    <jats:p>To use automated speech analysis to assess multiple sclerosis (MS) fatigue metrics.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods:<\/jats:title>\n                    <jats:p>Eighty-four PwMS completed scripted and spontaneous speech tasks; fatigue was assessed with Modified Fatigue Impact Scale (MFIS). Speech was processed using an automated speech analysis pipeline (ki elements: SIGMA speech processing library) to transcribe speech and extract features. Regression models assessed associations between speech features and fatigue and validated in a separate set of 30 participants.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results:<\/jats:title>\n                    <jats:p>\n                      Cohort characteristics were as follows: mean age 49.8 (standard deviation ( SD) = 13.6), 71.4% female, 85% relapsing-onset, median Expanded Disability Status Scale (EDSS) 2.5 (range: 0\u20136.5), mean MFIS 27.6 ( SD = 19.4), and 30% with MFIS &gt; 38. MFIS moderately correlated with pitch ( R = 0.32, p = 0.005), pause duration ( R = 0.33, p = 0.007), and utterance duration ( R = 0.31, p = 0.0111). A logistic model using speech features from multiple tasks accurately classified MFIS in training (area under the curve (AUC) = 0.95, R\n                      <jats:sup>2<\/jats:sup>\n                      = 0.59, p &lt; 0.001) and test sets (AUC = 0.93, R\n                      <jats:sup>2<\/jats:sup>\n                      = 0.54, p = 0.0222). Adjusting for EDSS, processing speed, and depression in sensitivity analyses did not impact model accuracy.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion:<\/jats:title>\n                    <jats:p>Fatigue may be assessed using simple, low-burden speech tasks that correlate with gold-standard subjective fatigue measures.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1177\/13524585241303855","type":"journal-article","created":{"date-parts":[[2024,12,18]],"date-time":"2024-12-18T02:44:41Z","timestamp":1734489881000},"page":"231-241","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":6,"title":["From \u201cinvisible\u201d to \u201caudible\u201d: Features extracted during simple speech tasks classify patient-reported fatigue in multiple sclerosis"],"prefix":"10.1177","volume":"31","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1976-3847","authenticated-orcid":false,"given":"Alyssa","family":"Nylander","sequence":"first","affiliation":[{"name":"UCSF Weill Institute for Neurosciences, San Francisco, CA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nikki","family":"Sisodia","sequence":"additional","affiliation":[{"name":"UCSF Weill Institute for Neurosciences, San Francisco, CA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kyra","family":"Henderson","sequence":"additional","affiliation":[{"name":"UCSF Weill Institute for Neurosciences, San Francisco, CA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jaeleene","family":"Wijangco","sequence":"additional","affiliation":[{"name":"UCSF Weill Institute for Neurosciences, San Francisco, CA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kanishka","family":"Koshal","sequence":"additional","affiliation":[{"name":"UCSF Weill Institute for Neurosciences, San Francisco, CA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shane","family":"Poole","sequence":"additional","affiliation":[{"name":"UCSF Weill Institute for Neurosciences, San Francisco, CA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Marcelo","family":"Dias","sequence":"additional","affiliation":[{"name":"ki elements GmbH, Saarbr\u00fccken, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nicklas","family":"Linz","sequence":"additional","affiliation":[{"name":"ki elements GmbH, Saarbr\u00fccken, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Johannes","family":"Tr\u00f6ger","sequence":"additional","affiliation":[{"name":"ki elements GmbH, Saarbr\u00fccken, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alexandra","family":"K\u00f6nig","sequence":"additional","affiliation":[{"name":"ki elements GmbH, Saarbr\u00fccken, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Helen","family":"Hayward-Koennecke","sequence":"additional","affiliation":[{"name":"F. 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