{"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\/da\/2024\/06\/ai-system-can-predict-how-anxious-you-are-from-reactions-to-photos\/","title":{"rendered":"AI-system kan forudsige, hvor nerv\u00f8s du er ud fra reaktioner p\u00e5 fotos"},"content":{"rendered":"

Forestil dig at kunne forudsige en persons angstniveau bare ved at f\u00e5 dem til at vurdere et par billeder og svare p\u00e5 nogle enkle sp\u00f8rgsm\u00e5l. <\/strong><\/p>\n

Det er pr\u00e6cis, hvad forskere fra University of Cincinnati og Northwestern University har opn\u00e5et med deres \"Comp Cog AI\"-system.\u00a0<\/span><\/p>\n

Ved at kombinere AI med videnskaben om, hvordan vores hjerner behandler information, har de skabt et v\u00e6rkt\u00f8j, der pr\u00e6cist kan identificere mennesker, som m\u00e5ske k\u00e6mper med angst.\u00a0<\/span><\/p>\n

Den <\/span>unders\u00f8gelse<\/span><\/a>som blev offentliggjort i Mental Health Research, involverede over 3.000 deltagere fra hele USA. <\/span><\/p>\n

Hver person vurderede en r\u00e6kke mildt f\u00f8lelsesladede billeder fra International Affective Picture System (IAPS) og gav grundl\u00e6ggende oplysninger om sig selv, f.eks. alder og oplevet ensomhed.\u00a0<\/span><\/p>\n

IAPS er udviklet af Center for the Study of Emotion and Attention ved University of Florida. Den indeholder et standardiseret s\u00e6t fotografier, der er vurderet for deres f\u00f8lelsesm\u00e6ssige indhold i form af valens (behag), arousal (intensitet) og dominans (kontrol).<\/p>\n

\"Ai-f\u00f8lelser\"
Et eksempel p\u00e5 et billede fra International Affective Picture System (IAPS). Kilde: Mental Health Research: Forskning i mental sundhed.<\/figcaption><\/figure>\n

AI-systemet analyserede derefter disse data og ledte efter m\u00f8nstre i den m\u00e5de, folk reagerede p\u00e5 billederne, og hvordan disse reaktioner var relateret til deres angstniveauer.\u00a0<\/span><\/p>\n

Efter tr\u00e6ning var Comp Cog AI-systemet i stand til at forudsige angst med op til 81% n\u00f8jagtighed, hvilket giver h\u00e5b om en fremtid, hvor psykiske problemer kan identificeres ved hj\u00e6lp af lette selvbetjeningssystemer.\u00a0<\/span><\/p>\n

Som hovedforfatter Sumra Bari <\/span>forklarer<\/span><\/a>\"Vi brugte minimale beregningsressourcer og et lille s\u00e6t variabler til at forudsige angstniveauer. Et vigtigt s\u00e6t af disse variabler kvantificerer processer, der er vigtige for d\u00f8mmekraften.\"<\/span><\/p>\n

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

Her kan du l\u00e6se mere om, hvordan unders\u00f8gelsen fungerede:<\/p>\n

    \n
  1. Indsamling af data<\/b>: Deltagerne gennemf\u00f8rte en billedvurderingsopgave, hvor de tildelte vurderinger fra -3 (kan ikke lide meget) til +3 (kan lide meget) til 48 mildt f\u00f8lelsesladede billeder fra IAPS. De besvarede ogs\u00e5 sp\u00f8rgsm\u00e5l om deres alder, oplevede ensomhed og demografiske oplysninger.<\/span><\/li>\n
  2. Udvinding af funktioner<\/b>: AI-systemet udtrak 15 vigtige vurderingsvariabler fra billedvurderingsdataene, s\u00e5som tabsaversion, risikoaversion og bel\u00f8nningsaversionskonsistens. Disse variabler kvantificerer sk\u00e6vheder i vurderinger af bel\u00f8nning\/aversion og er blevet forbundet med hjernesystemer, der er involveret i b\u00e5de vurdering og angst.<\/span><\/li>\n
  3. AI-tr\u00e6ning og -forudsigelse<\/b>: Forskerne brugte Random Forest og balancerede Random Forest maskinl\u00e6ringsalgoritmer til at tr\u00e6ne AI-systemet p\u00e5 en delm\u00e6ngde af dataene. AI'en brugte vurderingsvariablerne og de kontekstuelle faktorer til at forudsige hver deltagers angstniveau, som m\u00e5lt ved tilstandsangstdelen af State-Trait Anxiety Inventory (STAI).<\/span><\/li>\n
  4. Evaluering og fortolkning af modeller<\/b>: Det tr\u00e6nede AI-system blev testet p\u00e5 de resterende data for at vurdere dets n\u00f8jagtighed, sensitivitet og specificitet i forudsigelsen af angstniveauer. Forskerne udf\u00f8rte ogs\u00e5 medierings- og moderationsanalyser for at forst\u00e5, hvordan vurderingsvariablerne og de kontekstuelle faktorer interagerede for at modellere angst.<\/span><\/li>\n<\/ol>\n

    De fire vigtigste pr\u00e6diktorer - alder, ensomhed, husstandsindkomst og besk\u00e6ftigelsesstatus - bidrog med 29-31% af modellens forudsigelseskraft, mens de 15 vurderingsvariabler tilsammen bidrog med 55-61%.<\/span><\/p>\n

    Medforfatter Aggelos Katsaggelos fremh\u00e6vede betydningen af unders\u00f8gelsens tilgang og sagde: \"Brug af en billedvurderingsopgave med kontekstuelle variabler, der p\u00e5virker bed\u00f8mmelsen, kan virke enkel, men forst\u00e5else af m\u00f8nstre i pr\u00e6ferencer giver os mulighed for at afd\u00e6kke de kritiske komponenter for et stort s\u00e6t adf\u00e6rd.\"<\/span><\/p>\n

    Forskerne forestiller sig at udvikle Comp Cog AI-teknologien til en brugervenlig app til sundhedspersonale, hospitaler og endda milit\u00e6ret, s\u00e5 de hurtigt kan identificere personer med h\u00f8j risiko for angst.\u00a0<\/span><\/p>\n

    Som Bari bem\u00e6rker: \"Billedvurderingsopgaven kan bruges til at producere daglige og upartiske \u00f8jebliksbilleder af en persons mentale sundhedstilstand uden at stille direkte sp\u00f8rgsm\u00e5l, som kan udl\u00f8se negative eller forstyrrende f\u00f8lelser.\"\u00a0<\/span><\/p>\n

    Tidligere forskning udnyttede AI til at Hj\u00e6lp med at diagnosticere skizofreni<\/a>mens der er udviklet v\u00e6rkt\u00f8jer til at levere AI-terapi til mennesker med psykiske lidelser. gennem digitale avatarer<\/a>.\u00a0<\/span><\/p>","protected":false},"excerpt":{"rendered":"

    Forestil dig at kunne forudsige en persons angstniveau blot ved at f\u00e5 vedkommende til at vurdere et par billeder og svare p\u00e5 nogle enkle sp\u00f8rgsm\u00e5l. Det er pr\u00e6cis, hvad forskere fra University of Cincinnati og Northwestern University har opn\u00e5et med deres \"Comp Cog AI\"-system. Ved at kombinere AI med videnskaben om, hvordan vores hjerner behandler information, har de skabt et v\u00e6rkt\u00f8j, der pr\u00e6cist kan identificere mennesker, som m\u00e5ske k\u00e6mper med angst. Unders\u00f8gelsen, der blev offentliggjort i Mental Health Research, involverede over 3.000 deltagere fra hele USA. Hver person vurderede en r\u00e6kke mildt f\u00f8lelsesladede billeder fra International Affective Picture System (IAPS) og<\/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\/da\/2024\/06\/ai-system-can-predict-how-anxious-you-are-from-reactions-to-photos\/\" \/>\n<meta property=\"og:locale\" content=\"da_DK\" \/>\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\/da\/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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