{"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\/da\/2024\/07\/new-ai-model-successfully-identifies-alzheimers-disease-using-speech-analysis\/","title":{"rendered":"Nyt AI-system identificerer Alzheimers sygdom ved hj\u00e6lp af taleanalyse"},"content":{"rendered":"

Ved at analysere talem\u00f8nstre har forskere ved Boston University udviklet et AI-system, der med n\u00e6sten 80% n\u00f8jagtighed kan forudsige, om en person med mild kognitiv sv\u00e6kkelse vil udvikle Alzheimers sygdom inden for seks \u00e5r.<\/b><\/p>\n

Den <\/span>unders\u00f8gelse<\/span><\/a>som er offentliggjort i tidsskriftet Alzheimer's & Dementia, bruger kunstig intelligens til at udtr\u00e6kke v\u00e6rdifulde diagnostiske oplysninger fra kognitive vurderinger, hvilket fremskynder diagnosticeringen af Alzheimers og dermed behandlingen.\u00a0<\/span><\/p>\n

Teamets AI-model opn\u00e5ede en n\u00f8jagtighed p\u00e5 78,5% og en f\u00f8lsomhed p\u00e5 81,1% i forudsigelsen af udviklingen fra mild kognitiv sv\u00e6kkelse (MCI) til Alzheimers sygdom inden for en seks\u00e5rig tidsramme. Det sl\u00e5r andre traditionelle og ikke-invasive tests.<\/span><\/p>\n

Afg\u00f8rende er det dog, at systemet udelukkende baserer sig p\u00e5 let tilg\u00e6ngelige data: tale transskriberet fra kognitive vurderinger og grundl\u00e6ggende demografiske oplysninger som alder, k\u00f8n og uddannelsesniveau. <\/span><\/p>\n

Kognitive vurderinger som Boston Naming Test involverer en kliniker, der taler med patienten. Lyden fra disse tests optages ofte til videre analyse.\u00a0<\/span><\/p>\n

\"Vi ville gerne forudsige, hvad der ville ske i de n\u00e6ste seks \u00e5r - og vi fandt ud af, at vi med rimelighed kan lave den forudsigelse med relativt stor sikkerhed og n\u00f8jagtighed\". <\/span>sagde Ioannis (Yannis) Paschalidis<\/span><\/a>direkt\u00f8r for BU Rafik B. Hariri Institute for Computing and Computational Science & Engineering og en af unders\u00f8gelsens ledende forskere.<\/span><\/p>\n

\"Hvis man kan forudsige, hvad der vil ske, har man bedre mulighed for at gribe ind med medicin og i det mindste fors\u00f8ge at opretholde stabiliteten i tilstanden og forhindre overgangen til mere alvorlige former for demens.\"<\/span><\/p>\n

Mere om unders\u00f8gelsen<\/h2>\n

Her er en oversigt over, hvordan unders\u00f8gelsen fungerede:<\/span><\/p>\n

    \n
  1. Forskerteamet begyndte med at indsamle lydoptagelser af kognitive vurderinger fra 166 deltagere, der var diagnosticeret med mild kognitiv sv\u00e6kkelse (MCI). Derefter fulgte de disse personer over en seks\u00e5rig periode for at afg\u00f8re, hvem der udviklede sig til Alzheimers sygdom, og hvem der forblev stabile.<\/span><\/li>\n
  2. Teamet brugte avanceret talegenkendelsesteknologi til at transskribere lydoptagelserne og forberede dataene til analyse.\u00a0<\/span><\/li>\n
  3. Dern\u00e6st anvendte forskerne sofistikerede teknikker til behandling af naturligt sprog for at udtr\u00e6kke en lang r\u00e6kke sproglige tr\u00e6k og m\u00f8nstre, som de mente potentielt kunne tjene som indikatorer for Alzheimers risiko.<\/span><\/li>\n
  4. De brugte derefter talefunktionerne og demografiske oplysninger til at udvikle flere maskinl\u00e6ringsmodeller.<\/li>\n
  5. Disse AI-modeller blev designet til at forudsige sandsynligheden for, at en given person ville udvikle sig fra mild kognitiv sv\u00e6kkelse til Alzheimers sygdom baseret p\u00e5 deres unikke talem\u00f8nstre og personlige egenskaber.<\/span><\/li>\n
  6. Modellerne opn\u00e5ede en n\u00f8jagtighed p\u00e5 78,5% og en f\u00f8lsomhed p\u00e5 81,1% i forudsigelsen af, hvilke deltagere der ville udvikle Alzheimers inden for den seks\u00e5rige unders\u00f8gelsesperiode.<\/span><\/li>\n
  7. I en endelig analyse identificerede forskerholdet de kognitive tests, der havde st\u00f8rst forudsigelsesevne for Alzheimers-risiko, s\u00e5som Boston Naming Test, lighedstests og Wechsler Adult Intelligence Scale.<\/span><\/li>\n<\/ol>\n

    \"Det digitale er det nye blod\", siger Rhoda Au, professor ved BU's Chobanian & Avedisian School of Medicine og medforfatter til unders\u00f8gelsen.\u00a0<\/span><\/p>\n

    \"Man kan indsamle det, analysere det ud fra det, man ved i dag, gemme det og analysere det igen ud fra det nye, der dukker op i morgen.\"<\/span><\/p>\n

    Et af de mest interessante aspekter af unders\u00f8gelsen var, at visse dele af de kognitive vurderinger var s\u00e6rligt forudsigelige for den fremtidige risiko for Alzheimers.\u00a0<\/span><\/p>\n

    \"Vores analyse afsl\u00f8rede, at subtests relateret til demografiske sp\u00f8rgsm\u00e5l, Boston Naming Test, lighedstest og Wechsler Adult Intelligence Scale viste sig at v\u00e6re de bedste funktioner, der drev vores models ydeevne\", bem\u00e6rker forskerne.\u00a0<\/span><\/p>\n

    Det kan danne grundlag for udviklingen af mere m\u00e5lrettede kognitive vurderinger, som kan str\u00f8mline screeningsprocessen yderligere.<\/span><\/p>\n

    Selv om resultaterne er lovende, indr\u00f8mmer forskerne, at der er behov for yderligere validering i st\u00f8rre og mere forskelligartede populationer.\u00a0<\/span><\/p>\n

    Talegenkendelse kan \u00e5bne d\u00f8ren til tidlig diagnose<\/h2>\n

    Taleanalyse har vist sig at v\u00e6re en v\u00e6rdifuld teknik til at forudsige Alzheimers og andre sygdomme. <\/span><\/p>\n

    I en <\/span>2020-unders\u00f8gelse<\/span><\/a> I lighed med unders\u00f8gelsen fra Boston University demonstrerede forskere fra University of Sheffield deres AI's evne til at skelne mellem deltagere med Alzheimers sygdom eller mild kognitiv sv\u00e6kkelse og dem med funktionel kognitiv forstyrrelse eller raske kontrolpersoner med en n\u00f8jagtighed p\u00e5 86,7%.\u00a0<\/span><\/p>\n

    Forskere hos Klick Labs har ogs\u00e5 <\/span>udviklet en AI-model<\/span><\/a> der kan opdage type 2-diabetes ved hj\u00e6lp af korte stemmeoptagelser p\u00e5 kun 6 til 10 sekunder. <\/span>Fremskreden diabetes kan p\u00e5virke stemmen gennem nerveskader, nedsat blodgennemstr\u00f8mning og mundt\u00f8rhed, hvilket resulterer i synlige forandringer.\u00a0<\/span><\/p>\n

    Unders\u00f8gelsen analyserede 18.000 optagelser for at identificere subtile akustiske forskelle mellem diabetikere og ikke-diabetikere. <\/span><\/p>\n

    I kombination med faktorer som alder og BMI opn\u00e5ede modellen en maksimal testn\u00f8jagtighed p\u00e5 89% for kvinder og 86% for m\u00e6nd.<\/span><\/p>\n

    Tilsammen viser disse unders\u00f8gelser, at AI-st\u00f8ttede ikke-invasive tests og diagnostiske metoder kan f\u00f8re til hurtigere og mere effektiv behandling, selv n\u00e5r der ikke er speciall\u00e6ger og udstyr til stede.<\/p>","protected":false},"excerpt":{"rendered":"

    Ved at analysere talem\u00f8nstre har forskere ved Boston University udviklet et AI-system, der med n\u00e6sten 80% n\u00f8jagtighed kan forudsige, om en person med mild kognitiv sv\u00e6kkelse vil udvikle Alzheimers sygdom inden for seks \u00e5r. Unders\u00f8gelsen, der er offentliggjort i tidsskriftet Alzheimer's & Dementia, bruger AI til at udtr\u00e6kke v\u00e6rdifulde diagnostiske oplysninger fra kognitive vurderinger, hvilket fremskynder Alzheimers diagnose og dermed behandlingen. Teamets AI-model opn\u00e5ede en n\u00f8jagtighed p\u00e5 78,5% og en f\u00f8lsomhed p\u00e5 81,1% i forudsigelsen af udviklingen fra mild kognitiv sv\u00e6kkelse (MCI) til Alzheimers sygdom inden for en tidsramme p\u00e5 seks \u00e5r. Det sl\u00e5r andre traditionelle og ikke-invasive tests. Afg\u00f8rende er det dog, at systemet er afh\u00e6ngigt af<\/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":"\nNew AI system successfully identifies Alzheimer'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\/da\/2024\/07\/new-ai-model-successfully-identifies-alzheimers-disease-using-speech-analysis\/\" \/>\n<meta property=\"og:locale\" content=\"da_DK\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"New AI system successfully identifies Alzheimer'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’s disease within six years. The study, published in the journal Alzheimer’s & Dementia, uses AI to extract valuable diagnostic information from cognitive assessments, accelerating Alzheimer\u2019s diagnosis and, in turn, treatment.\u00a0 The team’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’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\/da\/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\" 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