{"id":12979,"date":"2024-06-20T16:15:39","date_gmt":"2024-06-20T16:15:39","guid":{"rendered":"https:\/\/dailyai.com\/?p=12979"},"modified":"2024-06-21T15:12:06","modified_gmt":"2024-06-21T15:12:06","slug":"ai-system-can-predict-how-anxious-you-are-from-reactions-to-photos","status":"publish","type":"post","link":"https:\/\/dailyai.com\/sv\/2024\/06\/ai-system-can-predict-how-anxious-you-are-from-reactions-to-photos\/","title":{"rendered":"AI-system kan f\u00f6ruts\u00e4ga hur orolig du \u00e4r utifr\u00e5n reaktioner p\u00e5 foton"},"content":{"rendered":"

T\u00e4nk dig att kunna f\u00f6ruts\u00e4ga n\u00e5gons \u00e5ngestniv\u00e5 bara genom att l\u00e5ta dem betygs\u00e4tta n\u00e5gra bilder och svara p\u00e5 n\u00e5gra enkla fr\u00e5gor. <\/strong><\/p>\n

Det \u00e4r precis vad forskare fr\u00e5n University of Cincinnati och Northwestern University har \u00e5stadkommit med sitt \"Comp Cog AI\"-system.\u00a0<\/span><\/p>\n

Genom att kombinera AI med vetenskapen om hur v\u00e5ra sinnen bearbetar information har de skapat ett verktyg som exakt kan identifiera personer som kanske k\u00e4mpar med \u00e5ngest.\u00a0<\/span><\/p>\n

Den <\/span>studie<\/span><\/a>som publicerades i Mental Health Research, omfattade \u00f6ver 3.000 deltagare fr\u00e5n hela USA. <\/span><\/p>\n

Varje person bed\u00f6mde en serie milt k\u00e4nslom\u00e4ssiga bilder fr\u00e5n International Affective Picture System (IAPS) och l\u00e4mnade grundl\u00e4ggande information om sig sj\u00e4lv, s\u00e5som \u00e5lder och upplevd ensamhet.\u00a0<\/span><\/p>\n

IAPS har utvecklats av Center for the Study of Emotion and Attention vid University of Florida. Den inneh\u00e5ller en standardiserad upps\u00e4ttning fotografier som bed\u00f6ms utifr\u00e5n sitt emotionella inneh\u00e5ll i termer av valens (behaglighet), upphetsning (intensitet) och dominans (kontroll).<\/p>\n

\"Ai-k\u00e4nslor\"
Ett exempel p\u00e5 en bild fr\u00e5n International Affective Picture System (IAPS). K\u00e4lla: Mental Health Research: Forskning om mental h\u00e4lsa.<\/figcaption><\/figure>\n

AI-systemet analyserade sedan dessa data och letade efter m\u00f6nster i hur m\u00e4nniskor reagerade p\u00e5 bilderna och hur dessa reaktioner var relaterade till deras \u00e5ngestniv\u00e5er.\u00a0<\/span><\/p>\n

Efter tr\u00e4ning kunde AI-systemet Comp Cog f\u00f6rutsp\u00e5 \u00e5ngest med upp till 81% noggrannhet, vilket ger hopp om en framtid d\u00e4r psykiska problem kan identifieras med hj\u00e4lp av l\u00e4tta sj\u00e4lvbetj\u00e4ningssystem.\u00a0<\/span><\/p>\n

Som huvudf\u00f6rfattare Sumra Bari <\/span>f\u00f6rklarar<\/span><\/a>, \"Vi anv\u00e4nde minimala ber\u00e4kningsresurser och en liten upps\u00e4ttning variabler f\u00f6r att f\u00f6ruts\u00e4ga \u00e5ngestniv\u00e5er. En viktig upps\u00e4ttning av dessa variabler kvantifierar processer som \u00e4r viktiga f\u00f6r omd\u00f6met.\"<\/span><\/p>\n

Mer om studien<\/h2>\n

H\u00e4r \u00e4r mer information om hur studien gick till:<\/p>\n

    \n
  1. Insamling av data<\/b>: Deltagarna genomf\u00f6rde en bildbed\u00f6mningsuppgift och tilldelade betyg fr\u00e5n -3 (tycker mycket illa om) till +3 (tycker mycket om) till 48 milt k\u00e4nslom\u00e4ssiga bilder fr\u00e5n IAPS. De svarade ocks\u00e5 p\u00e5 fr\u00e5gor om sin \u00e5lder, upplevd ensamhet och demografisk information.<\/span><\/li>\n
  2. Extrahering av funktioner<\/b>: AI-systemet extraherade 15 viktiga bed\u00f6mningsvariabler fr\u00e5n bildernas betygsdata, t.ex. f\u00f6rlustaversion, riskaversion och bel\u00f6ningsaversion. Dessa variabler kvantifierar skevheter i bed\u00f6mningar av bel\u00f6ning\/aversion och har kopplats till hj\u00e4rnsystem som \u00e4r inblandade i b\u00e5de bed\u00f6mning och \u00e5ngest.<\/span><\/li>\n
  3. AI-utbildning och prediktion<\/b>: Forskarna anv\u00e4nde maskininl\u00e4rningsalgoritmerna Random Forest och balanced Random Forest f\u00f6r att tr\u00e4na AI-systemet p\u00e5 en delm\u00e4ngd av data. AI anv\u00e4nde bed\u00f6mningsvariablerna och kontextuella faktorer f\u00f6r att f\u00f6ruts\u00e4ga varje deltagares \u00e5ngestniv\u00e5, m\u00e4tt med den statliga \u00e5ngestdelen av State-Trait Anxiety Inventory (STAI).<\/span><\/li>\n
  4. Utv\u00e4rdering och tolkning av modeller<\/b>: Det utbildade AI-systemet testades p\u00e5 de \u00e5terst\u00e5ende uppgifterna f\u00f6r att bed\u00f6ma dess noggrannhet, k\u00e4nslighet och specificitet n\u00e4r det g\u00e4ller att f\u00f6ruts\u00e4ga \u00e5ngestniv\u00e5er. Forskarna genomf\u00f6rde ocks\u00e5 medierings- och modereringsanalyser f\u00f6r att f\u00f6rst\u00e5 hur bed\u00f6mningsvariablerna och de kontextuella faktorerna samverkade f\u00f6r att modellera \u00e5ngest.<\/span><\/li>\n<\/ol>\n

    De fyra viktigaste prediktorerna - \u00e5lder, ensamhet, hush\u00e5llsinkomst och anst\u00e4llningsstatus - bidrog med 29-31% av modellens prediktiva kraft, medan de 15 bed\u00f6mningsvariablerna tillsammans bidrog med 55-61%.<\/span><\/p>\n

    F\u00f6rfattaren Aggelos Katsaggelos framh\u00f6ll betydelsen av studiens tillv\u00e4gag\u00e5ngss\u00e4tt och sa: \"Att anv\u00e4nda en bildbed\u00f6mningsuppgift med kontextuella variabler som p\u00e5verkar bed\u00f6mningen kan verka enkelt, men genom att f\u00f6rst\u00e5 m\u00f6nster i preferenser kan vi avsl\u00f6ja de kritiska komponenterna f\u00f6r en stor upps\u00e4ttning beteenden.\"<\/span><\/p>\n

    Forskarna t\u00e4nker sig att Comp Cogs AI-teknik ska utvecklas till en anv\u00e4ndarv\u00e4nlig app f\u00f6r v\u00e5rdgivare, sjukhus och till och med milit\u00e4ren f\u00f6r att snabbt kunna identifiera personer med h\u00f6g risk f\u00f6r \u00e5ngest.\u00a0<\/span><\/p>\n

    Som Bari konstaterar: \"Bildskattningsuppgiften kan anv\u00e4ndas f\u00f6r att ta fram dagliga och opartiska \u00f6gonblicksbilder av en persons psykiska h\u00e4lsa utan att st\u00e4lla direkta fr\u00e5gor som kan utl\u00f6sa negativa eller uppr\u00f6rande k\u00e4nslor.\"\u00a0<\/span><\/p>\n

    Tidigare forskning utnyttjade AI f\u00f6r att hj\u00e4lpa till att diagnostisera schizofreni<\/a>, medan verktyg har utvecklats f\u00f6r att leverera AI-terapi till personer med psykiska problem genom digitala avatarer<\/a>.\u00a0<\/span><\/p>","protected":false},"excerpt":{"rendered":"

    T\u00e4nk dig att kunna f\u00f6ruts\u00e4ga n\u00e5gons \u00e5ngestniv\u00e5 bara genom att l\u00e5ta dem betygs\u00e4tta n\u00e5gra bilder och svara p\u00e5 n\u00e5gra enkla fr\u00e5gor. Det \u00e4r precis vad forskare fr\u00e5n University of Cincinnati och Northwestern University har \u00e5stadkommit med sitt \"Comp Cog AI\"-system. Genom att kombinera AI med vetenskapen om hur v\u00e5ra sinnen bearbetar information har de skapat ett verktyg som exakt kan identifiera personer som kanske k\u00e4mpar med \u00e5ngest. Studien, som publicerades i Mental Health Research, involverade \u00f6ver 3 000 deltagare fr\u00e5n hela USA. Varje person bed\u00f6mde en serie milt k\u00e4nslom\u00e4ssiga bilder fr\u00e5n International Affective Picture System (IAPS) och<\/p>","protected":false},"author":2,"featured_media":13004,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[88],"tags":[178],"class_list":["post-12979","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-ethics","tag-medicine"],"yoast_head":"\nAI system can predict how anxious you are from reactions to photos | 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\/06\/ai-system-can-predict-how-anxious-you-are-from-reactions-to-photos\/\" \/>\n<meta property=\"og:locale\" content=\"sv_SE\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"AI system can predict how anxious you are from reactions to photos | DailyAI\" \/>\n<meta property=\"og:description\" content=\"Imagine being able to predict someone’s anxiety level just by having them rate a few pictures and answer some simple questions. That’s exactly what researchers from the University of Cincinnati and Northwestern University have accomplished with their “Comp Cog AI” system.\u00a0 By combining AI with the science of how our minds process information, they’ve created a tool that can accurately identify people who might be struggling with anxiety.\u00a0 The study, published in Mental Health Research, involved over 3,000 participants from across the US. Each person rated a series of mildly emotional images from the International Affective Picture System (IAPS) and\" \/>\n<meta property=\"og:url\" content=\"https:\/\/dailyai.com\/sv\/2024\/06\/ai-system-can-predict-how-anxious-you-are-from-reactions-to-photos\/\" \/>\n<meta property=\"og:site_name\" content=\"DailyAI\" \/>\n<meta property=\"article:published_time\" content=\"2024-06-20T16:15:39+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2024-06-21T15:12:06+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/dailyai.com\/wp-content\/uploads\/2024\/06\/DALL\u00b7E-2024-06-20-17.05.33-An-AI-system-analyzing-a-series-of-photos-to-predict-anxiety-levels.-The-scene-includes-a-computer-screen-displaying-multiple-facial-reactions-in-phot.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 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