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dc.rights.licenseopenen_US
hal.structure.identifierSommeil, Addiction et Neuropsychiatrie [Bordeaux] [SANPSY]
dc.contributor.authorMARTIN, Vincent P.
hal.structure.identifierLaboratoire Bordelais de Recherche en Informatique [LaBRI]
dc.contributor.authorROUAS, Jean-Luc
dc.date.accessioned2025-03-26T09:19:12Z
dc.date.available2025-03-26T09:19:12Z
dc.date.issued2024
dc.date.conference2024-05-20
dc.identifier.isbn978-2-493814-10-4en_US
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/205688
dc.description.abstractEnVoice biomarkers hold the promise of improving access to care and therapeutic follow-up for people with psychiatric disorders, tackling the issues raised by their high prevalence and the significant diagnostic delays and difficulties in patients follow-up. Yet, despite many years of successful research in the field, none of these voice biomarkers are implemented in clinical practice. Beyond the reductive explanation of the lack of explainability of the involved machine learning systems, we look for arguments in the epistemology and sociology of psychiatry. We show that the estimation of diagnoses, the major task in the literature, is of little interest to both clinicians and patients. After tackling the common misbeliefs about diagnosis in psychiatry in a didactic way, we propose a paradigm shift towards the estimation of clinical symptoms and signs, which not only address the limitations raised against diagnosis estimation but also enable the formulation of new machine learning tasks. We hope that this paradigm shift will empower the use of vocal biomarkers in clinical practice. It is however conditional on a change in database labeling practices, but also on a profound change in the speech processing community’s practices towards psychiatry.
dc.description.sponsorshipHealth, behaviors and autonomous digital technologies - ANR-22-PESN-0009en_US
dc.description.sponsorshipSanté Numérique en Société - ANR-22-PESN-0004en_US
dc.language.isoENen_US
dc.rightsAttribution-NonCommercial 3.0 United States*
dc.rights.urihttp://creativecommons.org/licenses/by-nc/3.0/us/*
dc.subject.enBiomarkers
dc.subject.enMachine Learning
dc.subject.enMental Health
dc.subject.enDiagnosis
dc.subject.enClinical Research
dc.subject.enParadigm Shifts
dc.subject.enAccess To Care
dc.subject.enClinical Practices
dc.subject.enCorpus Labeling
dc.subject.enFollow Up
dc.subject.enLabelings
dc.subject.enObjective Diagnosis
dc.subject.enPsychiatric Disorders
dc.subject.enSpeech Processing
dc.subject.enVoice Biomarker
dc.title.enWhy Voice Biomarkers of Psychiatric Disorders are not used in Clinical Practice? Deconstructing the Myth of the Need for Objective Diagnoses
dc.typeCommunication dans un congrèsen_US
dc.subject.halSciences du Vivant [q-bio]/Neurosciences [q-bio.NC]en_US
bordeaux.page17603 – 17613en_US
bordeaux.hal.laboratoriesSANPSY (Sommeil, Addiction, Neuropsychiatrie) - UMR 6033en_US
bordeaux.institutionUniversité de Bordeauxen_US
bordeaux.institutionCNRSen_US
bordeaux.conference.title2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)en_US
bordeaux.countryiten_US
bordeaux.conference.cityTurinen_US
bordeaux.identifier.funderIDHORIZON EUROPE Innovative Europeen_US
hal.proceedingsouien_US
hal.conference.organizerELRA Language Resources Associationen_US
hal.conference.organizerInternational Committee on Computational Linguistics (ICCL)en_US
hal.conference.end2024-05-25
hal.popularnonen_US
hal.audienceInternationaleen_US
hal.exportfalse
dc.rights.ccCC BY-NCen_US
bordeaux.COinSctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.date=2024&rft.spage=17603%20%E2%80%93%2017613&rft.epage=17603%20%E2%80%93%2017613&rft.au=MARTIN,%20Vincent%20P.&ROUAS,%20Jean-Luc&rft.isbn=978-2-493814-10-4&rft.genre=unknown


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