{"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\/sv\/2024\/07\/new-ai-model-successfully-identifies-alzheimers-disease-using-speech-analysis\/","title":{"rendered":"Nytt AI-system identifierar framg\u00e5ngsrikt Alzheimers sjukdom med hj\u00e4lp av talanalys"},"content":{"rendered":"

Genom att analysera talm\u00f6nster har forskare vid Boston University utvecklat ett AI-system som med n\u00e4stan 80% noggrannhet kan f\u00f6ruts\u00e4ga om en person med mild kognitiv neds\u00e4ttning kommer att utveckla Alzheimers sjukdom inom sex \u00e5r.<\/b><\/p>\n

Den <\/span>studie<\/span><\/a>som publicerades i tidskriften Alzheimer's & Dementia, anv\u00e4nder AI f\u00f6r att extrahera v\u00e4rdefull diagnostisk information fr\u00e5n kognitiva bed\u00f6mningar, vilket p\u00e5skyndar diagnostiseringen av Alzheimers sjukdom och i sin tur behandlingen.\u00a0<\/span><\/p>\n

Teamets AI-modell uppn\u00e5dde en noggrannhet p\u00e5 78,5% och en k\u00e4nslighet p\u00e5 81,1% n\u00e4r det g\u00e4llde att f\u00f6ruts\u00e4ga utvecklingen fr\u00e5n mild kognitiv st\u00f6rning (MCI) till Alzheimers sjukdom inom en sex\u00e5rsperiod. Detta sl\u00e5r andra traditionella och icke-invasiva tester.<\/span><\/p>\n

Avg\u00f6rande \u00e4r dock att systemet enbart f\u00f6rlitar sig p\u00e5 l\u00e4ttillg\u00e4ngliga data: tal som transkriberats fr\u00e5n kognitiva bed\u00f6mningar och grundl\u00e4ggande demografisk information som \u00e5lder, k\u00f6n och utbildningsniv\u00e5. <\/span><\/p>\n

Kognitiva utv\u00e4rderingar som Boston Naming Test inneb\u00e4r att en l\u00e4kare pratar med patienten. Ljudet fr\u00e5n dessa tester spelas ofta in f\u00f6r vidare analys.\u00a0<\/span><\/p>\n

\"Vi ville f\u00f6ruts\u00e4ga vad som skulle h\u00e4nda under de kommande sex \u00e5ren - och vi fann att vi rimligen kan g\u00f6ra den f\u00f6ruts\u00e4gelsen med relativt god s\u00e4kerhet och precision\", s\u00e4ger han. <\/span>sade Ioannis (Yannis) Paschalidis<\/span><\/a>, chef f\u00f6r BU Rafik B. Hariri Institute for Computing and Computational Science & Engineering och en av studiens huvudforskare.<\/span><\/p>\n

\"Om man kan f\u00f6ruts\u00e4ga vad som kommer att h\u00e4nda har man st\u00f6rre m\u00f6jlighet att ingripa med l\u00e4kemedel och \u00e5tminstone f\u00f6rs\u00f6ka bibeh\u00e5lla stabiliteten i tillst\u00e5ndet och f\u00f6rhindra \u00f6verg\u00e5ngen till sv\u00e5rare former av demens.\"<\/span><\/p>\n

Mer om studien<\/h2>\n

H\u00e4r f\u00f6ljer en sammanfattning av hur studien fungerade:<\/span><\/p>\n

    \n
  1. Forskargruppen b\u00f6rjade med att samla in ljudinspelningar av kognitiva bed\u00f6mningar fr\u00e5n 166 deltagare som diagnostiserats med mild kognitiv st\u00f6rning (MCI). De f\u00f6ljde sedan dessa personer under en sex\u00e5rsperiod f\u00f6r att avg\u00f6ra vilka som utvecklades till Alzheimers sjukdom och vilka som f\u00f6rblev stabila.<\/span><\/li>\n
  2. Teamet anv\u00e4nde avancerad taligenk\u00e4nningsteknik f\u00f6r att transkribera ljudinspelningarna och f\u00f6rbereda data f\u00f6r analys.\u00a0<\/span><\/li>\n
  3. D\u00e4refter anv\u00e4nde forskarna sofistikerade tekniker f\u00f6r bearbetning av naturligt spr\u00e5k f\u00f6r att extrahera ett brett spektrum av spr\u00e5kliga drag och m\u00f6nster som de trodde potentiellt kunde fungera som indikatorer p\u00e5 Alzheimers risk.<\/span><\/li>\n
  4. De anv\u00e4nde sedan talegenskaperna och den demografiska informationen f\u00f6r att utveckla flera maskininl\u00e4rningsmodeller.<\/li>\n
  5. Dessa AI-modeller var utformade f\u00f6r att f\u00f6rutse sannolikheten f\u00f6r att en viss individ skulle utvecklas fr\u00e5n mild kognitiv st\u00f6rning till Alzheimers sjukdom baserat p\u00e5 deras unika talm\u00f6nster och personliga egenskaper.<\/span><\/li>\n
  6. Modellerna uppn\u00e5dde en tr\u00e4ffs\u00e4kerhet p\u00e5 78,5% och en k\u00e4nslighet p\u00e5 81,1% n\u00e4r det g\u00e4llde att f\u00f6ruts\u00e4ga vilka deltagare som skulle utveckla Alzheimers sjukdom inom den sex\u00e5riga studieperioden.<\/span><\/li>\n
  7. I en slutlig analys identifierade forskargruppen de kognitiva tester som hade st\u00f6rst f\u00f6rm\u00e5ga att f\u00f6ruts\u00e4ga risken f\u00f6r Alzheimers sjukdom, t.ex. Boston Naming Test, likhetstest och Wechsler Adult Intelligence Scale.<\/span><\/li>\n<\/ol>\n

    \"Det digitala \u00e4r det nya blodet\", s\u00e4ger Rhoda Au, professor vid BU:s Chobanian & Avedisian School of Medicine och medf\u00f6rfattare till studien.\u00a0<\/span><\/p>\n

    \"Du kan samla in den, analysera den utifr\u00e5n vad som \u00e4r k\u00e4nt idag, lagra den och analysera den p\u00e5 nytt utifr\u00e5n vad som \u00e4r nytt imorgon.\"<\/span><\/p>\n

    En av de mest intressanta aspekterna av studien var att vissa delar av de kognitiva bed\u00f6mningarna var s\u00e4rskilt prediktiva f\u00f6r framtida risk f\u00f6r Alzheimers sjukdom.\u00a0<\/span><\/p>\n

    \"V\u00e5r analys visade att deltester relaterade till demografiska fr\u00e5gor, Boston Naming Test, likhetstester och Wechsler Adult Intelligence Scale var de viktigaste faktorerna f\u00f6r att v\u00e5r modell skulle fungera\", konstaterar forskarna.\u00a0<\/span><\/p>\n

    Detta skulle kunna ligga till grund f\u00f6r utvecklingen av mer m\u00e5linriktade kognitiva bed\u00f6mningar, vilket ytterligare skulle effektivisera screeningprocessen.<\/span><\/p>\n

    \u00c4ven om resultaten \u00e4r lovande medger forskarna att det finns behov av ytterligare validering i st\u00f6rre och mer varierade populationer.\u00a0<\/span><\/p>\n

    Taligenk\u00e4nning kan \u00f6ppna d\u00f6rren till tidig diagnos<\/h2>\n

    Talanalys har visat sig vara en v\u00e4rdefull teknik f\u00f6r att f\u00f6ruts\u00e4ga Alzheimers och andra sjukdomar. <\/span><\/p>\n

    I en <\/span>2020 \u00e5rs studie<\/span><\/a> I likhet med studien vid Boston University visade forskare vid University of Sheffield att deras AI kunde skilja mellan deltagare med Alzheimers sjukdom eller mild kognitiv st\u00f6rning och deltagare med funktionell kognitiv st\u00f6rning eller friska kontroller med en noggrannhet p\u00e5 86,7%.\u00a0<\/span><\/p>\n

    Forskare vid Klick Labs har ocks\u00e5 <\/span>utvecklat en AI-modell<\/span><\/a> som kan uppt\u00e4cka typ 2-diabetes med hj\u00e4lp av korta r\u00f6stinspelningar p\u00e5 bara 6 till 10 sekunder. <\/span>Avancerad diabetes kan p\u00e5verka r\u00f6sten genom nervskador, f\u00f6rs\u00e4mrat blodfl\u00f6de och muntorrhet, vilket kan leda till p\u00e5tagliga f\u00f6r\u00e4ndringar.\u00a0<\/span><\/p>\n

    I studien analyserades 18.000 inspelningar f\u00f6r att identifiera subtila akustiska skillnader mellan diabetiker och icke-diabetiker. <\/span><\/p>\n

    I kombination med faktorer som \u00e5lder och BMI uppn\u00e5dde modellen en maximal testprecision p\u00e5 89% f\u00f6r kvinnor och 86% f\u00f6r m\u00e4n.<\/span><\/p>\n

    Tillsammans visar dessa studier att AI-st\u00f6dda icke-invasiva tester och diagnostiska metoder kan leda till snabbare och effektivare behandling, \u00e4ven n\u00e4r specialistl\u00e4kare och utrustning saknas.<\/p>","protected":false},"excerpt":{"rendered":"

    Genom att analysera talm\u00f6nster har forskare vid Boston University utvecklat ett AI-system som med n\u00e4stan 80% noggrannhet kan f\u00f6ruts\u00e4ga om en person med mild kognitiv st\u00f6rning kommer att utveckla Alzheimers sjukdom inom sex \u00e5r. Studien, som publicerades i tidskriften Alzheimer's & Dementia, anv\u00e4nder AI f\u00f6r att extrahera v\u00e4rdefull diagnostisk information fr\u00e5n kognitiva bed\u00f6mningar, vilket p\u00e5skyndar diagnosen av Alzheimers sjukdom och i sin tur behandlingen. Teamets AI-modell uppn\u00e5dde en noggrannhet p\u00e5 78,5% och en k\u00e4nslighet p\u00e5 81,1% n\u00e4r det g\u00e4llde att f\u00f6ruts\u00e4ga utvecklingen fr\u00e5n mild kognitiv st\u00f6rning (MCI) till Alzheimers sjukdom inom en sex\u00e5rsperiod. Detta sl\u00e5r andra traditionella och icke-invasiva tester. Avg\u00f6rande \u00e4r dock att systemet f\u00f6rlitar sig p\u00e5<\/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\/sv\/2024\/07\/new-ai-model-successfully-identifies-alzheimers-disease-using-speech-analysis\/\" \/>\n<meta property=\"og:locale\" content=\"sv_SE\" \/>\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\/sv\/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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