{"id":13265,"date":"2024-07-04T18:38:04","date_gmt":"2024-07-04T18:38:04","guid":{"rendered":"https:\/\/dailyai.com\/?p=13265"},"modified":"2024-07-04T23:28:31","modified_gmt":"2024-07-04T23:28:31","slug":"new-ai-model-successfully-identifies-alzheimers-disease-using-speech-analysis","status":"publish","type":"post","link":"https:\/\/dailyai.com\/nb\/2024\/07\/new-ai-model-successfully-identifies-alzheimers-disease-using-speech-analysis\/","title":{"rendered":"Nytt AI-system identifiserer Alzheimers sykdom ved hjelp av taleanalyse"},"content":{"rendered":"<p><b>Ved \u00e5 analysere talem\u00f8nstre har forskere ved Boston University utviklet et AI-system som med nesten 80% n\u00f8yaktighet kan forutsi om en person med mild kognitiv svikt vil utvikle Alzheimers sykdom i l\u00f8pet av seks \u00e5r.<\/b><\/p>\n<p><span style=\"font-weight: 400;\">Den <\/span><a href=\"https:\/\/alz-journals.onlinelibrary.wiley.com\/doi\/10.1002\/alz.13886\" target=\"_blank\" rel=\"noopener\"><span style=\"font-weight: 400;\">studie<\/span><\/a><span style=\"font-weight: 400;\">publisert i tidsskriftet Alzheimer's &amp; Dementia, bruker kunstig intelligens til \u00e5 hente ut verdifull diagnostisk informasjon fra kognitive vurderinger, noe som kan fremskynde diagnostisering og behandling av Alzheimers sykdom.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Teamets AI-modell oppn\u00e5dde en n\u00f8yaktighet p\u00e5 78,5% og en sensitivitet p\u00e5 81,1% n\u00e5r det gjaldt \u00e5 forutsi utviklingen fra mild kognitiv svikt (MCI) til Alzheimers sykdom innenfor en tidsramme p\u00e5 seks \u00e5r. Dette sl\u00e5r andre tradisjonelle og ikke-invasive tester.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Det avgj\u00f8rende er imidlertid at systemet utelukkende baserer seg p\u00e5 lett tilgjengelige data: transkribert tale fra kognitive vurderinger og grunnleggende demografisk informasjon som alder, kj\u00f8nn og utdanningsniv\u00e5. <\/span><\/p>\n<p><span style=\"font-weight: 400;\">Kognitive tester som Boston Naming Test inneb\u00e6rer at en kliniker snakker med pasienten. Lyden fra disse testene blir ofte tatt opp for videre analyse.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">\"Vi \u00f8nsket \u00e5 forutsi hva som ville skje de neste seks \u00e5rene - og vi fant ut at vi kan forutsi dette med relativt god sikkerhet og n\u00f8yaktighet\", sier han. <\/span><a href=\"https:\/\/www.bu.edu\/articles\/2024\/new-ai-program-could-predict-alzheimers-disease\/\" target=\"_blank\" rel=\"noopener\"><span style=\"font-weight: 400;\">sa Ioannis (Yannis) Paschalidis<\/span><\/a><span style=\"font-weight: 400;\">, direkt\u00f8r for BU Rafik B. Hariri Institute for Computing and Computational Science &amp; Engineering og en av studiens ledende forskere.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">\"Hvis du kan forutsi hva som vil skje, har du st\u00f8rre mulighet og et tidsvindu til \u00e5 gripe inn med medisiner, og i det minste pr\u00f8ve \u00e5 opprettholde stabiliteten i tilstanden og forhindre overgangen til mer alvorlige former for demens.\"<\/span><\/p>\n<h2>Mer om studien<\/h2>\n<p><span style=\"font-weight: 400;\">Her er en oversikt over hvordan studien fungerte:<\/span><\/p>\n<ol>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Forskerteamet begynte med \u00e5 samle inn lydopptak av kognitive vurderinger fra 166 deltakere med diagnosen mild kognitiv svikt (MCI). Deretter fulgte de disse personene over en seks\u00e5rsperiode for \u00e5 finne ut hvem som utviklet Alzheimers sykdom og hvem som forble stabile.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Teamet brukte avansert talegjenkjenningsteknologi til \u00e5 transkribere lydopptakene og forberede dataene for analyse.\u00a0<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Deretter brukte forskerne sofistikerte teknikker for naturlig spr\u00e5kbehandling for \u00e5 trekke ut et bredt spekter av spr\u00e5klige trekk og m\u00f8nstre som de mente potensielt kunne fungere som indikatorer p\u00e5 Alzheimers-risiko.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Deretter brukte de talefunksjonene og den demografiske informasjonen til \u00e5 utvikle flere maskinl\u00e6ringsmodeller.<\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Disse AI-modellene ble utviklet for \u00e5 forutsi sannsynligheten for at en gitt person ville utvikle seg fra mild kognitiv svikt til Alzheimers sykdom, basert p\u00e5 deres unike talem\u00f8nstre og personlige egenskaper.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Modellene oppn\u00e5dde en n\u00f8yaktighet p\u00e5 78,5% og en sensitivitet p\u00e5 81,1% n\u00e5r det gjaldt \u00e5 forutsi hvilke deltakere som ville utvikle Alzheimers sykdom i l\u00f8pet av den seks \u00e5r lange studieperioden.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">I en endelig analyse identifiserte forskerteamet de kognitive testene som hadde st\u00f8rst prediksjonskraft for Alzheimers-risiko, slik som Boston Naming Test, likhetstester og Wechsler Adult Intelligence Scale.<\/span><\/li>\n<\/ol>\n<p><span style=\"font-weight: 400;\">\"Det digitale er det nye blodet\", sier Rhoda Au, professor ved BU's Chobanian &amp; Avedisian School of Medicine og medforfatter av studien.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">\"Du kan samle det inn, analysere det som er kjent i dag, lagre det og analysere det p\u00e5 nytt for \u00e5 finne ut hva som m\u00e5tte dukke opp i morgen.\"<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Et av de mest interessante aspektene ved studien var at visse deler av de kognitive vurderingene var spesielt prediktive for fremtidig Alzheimers-risiko.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">\"Analysen v\u00e5r viste at deltester knyttet til demografiske sp\u00f8rsm\u00e5l, Boston Naming Test, likhetstester og Wechsler Adult Intelligence Scale var de viktigste faktorene som drev resultatene til modellen v\u00e5r\", skriver forskerne.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Dette kan bidra til \u00e5 utvikle mer m\u00e5lrettede kognitive vurderinger, noe som kan effektivisere screeningprosessen ytterligere.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Selv om resultatene er lovende, innr\u00f8mmer forskerne at det er behov for ytterligere validering i st\u00f8rre og mer varierte populasjoner.\u00a0<\/span><\/p>\n<h2>Talegjenkjenning kan \u00e5pne d\u00f8ren til tidlig diagnose<\/h2>\n<p><span style=\"font-weight: 400;\">Taleanalyse har vist seg \u00e5 v\u00e6re en verdifull teknikk for \u00e5 forutsi Alzheimers og andre sykdommer. <\/span><\/p>\n<p><span style=\"font-weight: 400;\">I en <\/span><a href=\"https:\/\/dailyai.com\/nb\/2024\/01\/innovative-ai-tool-cognospeak-promises-faster-dementia-diagnosis\/\"><span style=\"font-weight: 400;\">2020-studie<\/span><\/a><span style=\"font-weight: 400;\"> I likhet med studien fra Boston University viste forskerne ved University of Sheffield at deres AI var i stand til \u00e5 skille mellom deltakere med Alzheimers sykdom eller mild kognitiv svikt og deltakere med funksjonell kognitiv forstyrrelse eller friske kontrollpersoner med en n\u00f8yaktighet p\u00e5 86,7%.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Forskere ved Klick Labs har ogs\u00e5 <\/span><a href=\"https:\/\/dailyai.com\/nb\/2023\/10\/researchers-diagnose-diabetes-in-seconds-using-voice-recordings\/\"><span style=\"font-weight: 400;\">utviklet en AI-modell<\/span><\/a><span style=\"font-weight: 400;\"> som kan oppdage type 2-diabetes ved hjelp av korte stemmeopptak p\u00e5 bare 6 til 10 sekunder. <\/span><span style=\"font-weight: 400;\">Avansert diabetes kan p\u00e5virke stemmen gjennom nerveskader, nedsatt blodgjennomstr\u00f8mning og munnt\u00f8rrhet, noe som kan f\u00f8re til p\u00e5viselige forandringer.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Studien analyserte 18 000 lydopptak for \u00e5 identifisere subtile akustiske forskjeller mellom personer med og uten diabetes. <\/span><\/p>\n<p><span style=\"font-weight: 400;\">I kombinasjon med faktorer som alder og BMI oppn\u00e5dde modellen en maksimal testn\u00f8yaktighet p\u00e5 89% for kvinner og 86% for menn.<\/span><\/p>\n<p>Til sammen viser disse studiene at KI-st\u00f8ttede ikke-invasive tester og diagnostiske metoder kan f\u00f8re til raskere og mer effektiv behandling, selv n\u00e5r spesialistleger og utstyr er frav\u00e6rende.<\/p>","protected":false},"excerpt":{"rendered":"<p>Ved \u00e5 analysere talem\u00f8nstre har forskere ved Boston University utviklet et AI-system som med nesten 80% n\u00f8yaktighet kan forutsi om en person med mild kognitiv svikt vil utvikle Alzheimers sykdom i l\u00f8pet av seks \u00e5r. Studien, som er publisert i tidsskriftet Alzheimer's &amp; Dementia, bruker kunstig intelligens til \u00e5 trekke ut verdifull diagnostisk informasjon fra kognitive vurderinger, noe som kan fremskynde diagnostisering og behandling av Alzheimers sykdom.  Teamets AI-modell oppn\u00e5dde en n\u00f8yaktighet p\u00e5 78,5% og en sensitivitet p\u00e5 81,1% n\u00e5r det gjaldt \u00e5 forutsi utviklingen fra mild kognitiv svikt (MCI) til Alzheimers sykdom innen en tidsramme p\u00e5 seks \u00e5r. Dette sl\u00e5r andre tradisjonelle og ikke-invasive tester. Det avgj\u00f8rende er imidlertid at systemet er avhengig av<\/p>","protected":false},"author":2,"featured_media":13269,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[88],"tags":[353,204,178],"class_list":["post-13265","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-ethics","tag-biology","tag-healthcare","tag-medicine"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.4 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>New AI system successfully identifies Alzheimer&#039;s disease using speech analysis | DailyAI<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/dailyai.com\/nb\/2024\/07\/new-ai-model-successfully-identifies-alzheimers-disease-using-speech-analysis\/\" \/>\n<meta property=\"og:locale\" content=\"nb_NO\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"New AI system successfully identifies Alzheimer&#039;s disease using speech analysis | DailyAI\" \/>\n<meta property=\"og:description\" content=\"By analyzing speech patterns, researchers at Boston University have developed an AI system that can predict with nearly 80% accuracy whether someone with mild cognitive impairment will develop Alzheimer&#8217;s disease within six years. The study, published in the journal Alzheimer&#8217;s &amp; Dementia, uses AI to extract valuable diagnostic information from cognitive assessments, accelerating Alzheimer\u2019s diagnosis and, in turn, treatment.\u00a0 The team&#8217;s AI model achieved an accuracy of 78.5% and a sensitivity of 81.1% in predicting progression from mild cognitive impairment (MCI) to Alzheimer&#8217;s disease within a six-year timeframe. This beats other traditional and non-invasive tests. Crucially, though, the system relies\" \/>\n<meta property=\"og:url\" content=\"https:\/\/dailyai.com\/nb\/2024\/07\/new-ai-model-successfully-identifies-alzheimers-disease-using-speech-analysis\/\" \/>\n<meta property=\"og:site_name\" content=\"DailyAI\" \/>\n<meta property=\"article:published_time\" content=\"2024-07-04T18:38:04+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2024-07-04T23:28:31+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/dailyai.com\/wp-content\/uploads\/2024\/07\/DALL\u00b7E-2024-07-04-19.41.55-A-high-quality-landscape-image-of-an-AI-brain-analyzing-speech-patterns-to-identify-Alzheimers-disease.-The-scene-is-simple-and-futuristic-featurin.webp\" \/>\n\t<meta property=\"og:image:width\" content=\"1792\" \/>\n\t<meta property=\"og:image:height\" content=\"1024\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/webp\" \/>\n<meta name=\"author\" content=\"Sam Jeans\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:creator\" content=\"@DailyAIOfficial\" \/>\n<meta name=\"twitter:site\" content=\"@DailyAIOfficial\" \/>\n<meta name=\"twitter:label1\" content=\"Skrevet av\" \/>\n\t<meta name=\"twitter:data1\" content=\"Sam Jeans\" \/>\n\t<meta name=\"twitter:label2\" content=\"Ansl. lesetid\" \/>\n\t<meta name=\"twitter:data2\" content=\"4 minutter\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\\\/\\\/schema.org\",\"@graph\":[{\"@type\":\"NewsArticle\",\"@id\":\"https:\\\/\\\/dailyai.com\\\/2024\\\/07\\\/new-ai-model-successfully-identifies-alzheimers-disease-using-speech-analysis\\\/#article\",\"isPartOf\":{\"@id\":\"https:\\\/\\\/dailyai.com\\\/2024\\\/07\\\/new-ai-model-successfully-identifies-alzheimers-disease-using-speech-analysis\\\/\"},\"author\":{\"name\":\"Sam Jeans\",\"@id\":\"https:\\\/\\\/dailyai.com\\\/#\\\/schema\\\/person\\\/711e81f945549438e8bbc579efdeb3c9\"},\"headline\":\"New AI system successfully identifies Alzheimer&#8217;s disease using speech analysis\",\"datePublished\":\"2024-07-04T18:38:04+00:00\",\"dateModified\":\"2024-07-04T23:28:31+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\\\/\\\/dailyai.com\\\/2024\\\/07\\\/new-ai-model-successfully-identifies-alzheimers-disease-using-speech-analysis\\\/\"},\"wordCount\":764,\"publisher\":{\"@id\":\"https:\\\/\\\/dailyai.com\\\/#organization\"},\"image\":{\"@id\":\"https:\\\/\\\/dailyai.com\\\/2024\\\/07\\\/new-ai-model-successfully-identifies-alzheimers-disease-using-speech-analysis\\\/#primaryimage\"},\"thumbnailUrl\":\"https:\\\/\\\/dailyai.com\\\/wp-content\\\/uploads\\\/2024\\\/07\\\/DALL\u00b7E-2024-07-04-19.41.55-A-high-quality-landscape-image-of-an-AI-brain-analyzing-speech-patterns-to-identify-Alzheimers-disease.-The-scene-is-simple-and-futuristic-featurin.webp\",\"keywords\":[\"Biology\",\"Healthcare\",\"Medicine\"],\"articleSection\":[\"Ethics &amp; 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When he\u2019s not writing, he can be found reading medical journals or digging through boxes of vinyl records.\",\"sameAs\":[\"https:\\\/\\\/www.linkedin.com\\\/in\\\/sam-jeans-6746b9142\\\/\"],\"url\":\"https:\\\/\\\/dailyai.com\\\/nb\\\/author\\\/samjeans\\\/\"}]}<\/script>\n<!-- \/ Yoast SEO plugin. -->","yoast_head_json":{"title":"Nytt AI-system identifiserer Alzheimers sykdom ved hjelp av taleanalyse | DailyAI","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/dailyai.com\/nb\/2024\/07\/new-ai-model-successfully-identifies-alzheimers-disease-using-speech-analysis\/","og_locale":"nb_NO","og_type":"article","og_title":"New AI system successfully identifies Alzheimer's disease using speech analysis | DailyAI","og_description":"By analyzing speech patterns, researchers at Boston University have developed an AI system that can predict with nearly 80% accuracy whether someone with mild cognitive impairment will develop Alzheimer&#8217;s disease within six years. The study, published in the journal Alzheimer&#8217;s &amp; Dementia, uses AI to extract valuable diagnostic information from cognitive assessments, accelerating Alzheimer\u2019s diagnosis and, in turn, treatment.\u00a0 The team&#8217;s AI model achieved an accuracy of 78.5% and a sensitivity of 81.1% in predicting progression from mild cognitive impairment (MCI) to Alzheimer&#8217;s disease within a six-year timeframe. This beats other traditional and non-invasive tests. 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