{"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\/it\/2024\/06\/ai-system-can-predict-how-anxious-you-are-from-reactions-to-photos\/","title":{"rendered":"Un sistema di intelligenza artificiale \u00e8 in grado di prevedere l'ansia in base alle reazioni alle foto"},"content":{"rendered":"

Immaginate di poter prevedere il livello di ansia di una persona semplicemente facendole valutare alcune immagini e rispondendo ad alcune semplici domande. <\/strong><\/p>\n

Questo \u00e8 esattamente ci\u00f2 che i ricercatori dell'Universit\u00e0 di Cincinnati e della Northwestern University hanno realizzato con il loro sistema \"Comp Cog AI\".\u00a0<\/span><\/p>\n

Combinando l'intelligenza artificiale con la scienza del modo in cui la nostra mente elabora le informazioni, hanno creato uno strumento in grado di identificare con precisione le persone che potrebbero soffrire di ansia.\u00a0<\/span><\/p>\n

Il <\/span>studio<\/span><\/a>pubblicato su Mental Health Research, ha coinvolto oltre 3.000 partecipanti provenienti da tutti gli Stati Uniti. <\/span><\/p>\n

Ogni persona ha valutato una serie di immagini leggermente emotive tratte dall'International Affective Picture System (IAPS) e ha fornito informazioni di base su di s\u00e9, come l'et\u00e0 e la solitudine percepita.\u00a0<\/span><\/p>\n

L'IAPS \u00e8 stato sviluppato dal Center for the Study of Emotion and Attention dell'Universit\u00e0 della Florida. Fornisce una serie standardizzata di fotografie valutate per il loro contenuto emotivo in termini di valenza (piacevolezza), eccitazione (intensit\u00e0) e dominanza (controllo).<\/p>\n

\"Emozioni\"
Un esempio di immagine dell'International Affective Picture System (IAPS). Fonte: Ricerca sulla salute mentale.<\/figcaption><\/figure>\n

Il sistema di intelligenza artificiale ha poi analizzato questi dati, cercando modelli nel modo in cui le persone rispondevano alle immagini e come queste risposte erano correlate ai loro livelli di ansia.\u00a0<\/span><\/p>\n

Dopo l'addestramento, il sistema Comp Cog AI \u00e8 stato in grado di prevedere l'ansia con un'accuratezza fino a 81%, offrendo una speranza per un futuro in cui i problemi di salute mentale possono essere identificati utilizzando sistemi leggeri e self-service.\u00a0<\/span><\/p>\n

L'autrice principale Sumra Bari <\/span>spiega<\/span><\/a>Abbiamo utilizzato risorse computazionali minime e un piccolo insieme di variabili per prevedere i livelli di ansia. Una serie importante di queste variabili quantifica processi importanti per il giudizio\".<\/span><\/p>\n

Per saperne di pi\u00f9 sullo studio<\/h2>\n

Ecco di pi\u00f9 su come ha funzionato lo studio:<\/p>\n

    \n
  1. Raccolta dati<\/b>: I partecipanti hanno completato un compito di valutazione delle immagini, assegnando valutazioni da -3 (non mi piace molto) a +3 (mi piace molto) a 48 immagini lievemente emotive dell'IAPS. Hanno inoltre risposto a domande sulla loro et\u00e0, sulla solitudine percepita e su informazioni demografiche.<\/span><\/li>\n
  2. Estrazione delle caratteristiche<\/b>: Il sistema di intelligenza artificiale ha estratto 15 variabili di giudizio chiave dai dati di valutazione delle immagini, come l'avversione alle perdite, l'avversione al rischio e la coerenza con l'avversione alla ricompensa. Queste variabili quantificano le distorsioni nei giudizi di ricompensa\/avversione e sono state collegate a sistemi cerebrali implicati sia nel giudizio che nell'ansia.<\/span><\/li>\n
  3. Formazione e previsione dell'intelligenza artificiale<\/b>: I ricercatori hanno utilizzato gli algoritmi di apprendimento automatico Random Forest e Random Forest bilanciato per addestrare il sistema AI su un sottoinsieme di dati. L'intelligenza artificiale ha utilizzato le variabili di giudizio e i fattori contestuali per prevedere il livello di ansia di ciascun partecipante, misurato dalla parte dell'ansia di stato dello State-Trait Anxiety Inventory (STAI).<\/span><\/li>\n
  4. Valutazione e interpretazione del modello<\/b>: Il sistema di intelligenza artificiale addestrato \u00e8 stato testato sui dati rimanenti per valutarne l'accuratezza, la sensibilit\u00e0 e la specificit\u00e0 nel prevedere i livelli di ansia. I ricercatori hanno anche condotto analisi di mediazione e moderazione per capire come le variabili di giudizio e i fattori contestuali interagissero per modellare l'ansia.<\/span><\/li>\n<\/ol>\n

    I quattro predittori pi\u00f9 importanti - et\u00e0, solitudine, reddito familiare e stato occupazionale - hanno contribuito per 29-31% al potere predittivo del modello, mentre le 15 variabili di giudizio hanno contribuito collettivamente per 55-61%.<\/span><\/p>\n

    Il coautore Aggelos Katsaggelos ha sottolineato l'importanza dell'approccio dello studio, affermando: \"L'uso di un compito di valutazione delle immagini con variabili contestuali che influenzano il giudizio pu\u00f2 sembrare semplice, ma la comprensione dei modelli di preferenza ci permette di scoprire le componenti critiche per un ampio insieme di comportamenti\".<\/span><\/p>\n

    I ricercatori prevedono di sviluppare la tecnologia Comp Cog AI in un'applicazione di facile utilizzo per gli operatori sanitari, gli ospedali e persino le forze armate per identificare rapidamente le persone ad alto rischio di ansia.\u00a0<\/span><\/p>\n

    Come osserva Bari, \"il compito di valutazione delle immagini pu\u00f2 essere utilizzato per produrre istantanee quotidiane e imparziali dello stato di salute mentale di una persona senza porre domande dirette che potrebbero innescare sentimenti negativi o sconvolgenti\".\u00a0<\/span><\/p>\n

    Le ricerche precedenti hanno sfruttato l'intelligenza artificiale per aiutare a diagnosticare la schizofrenia<\/a>mentre sono stati sviluppati strumenti per fornire terapie di intelligenza artificiale a persone con problemi di salute mentale. attraverso avatar digitali<\/a>.\u00a0<\/span><\/p>","protected":false},"excerpt":{"rendered":"

    Immaginate di poter prevedere il livello di ansia di una persona semplicemente facendole valutare alcune immagini e rispondendo ad alcune semplici domande. Questo \u00e8 esattamente ci\u00f2 che i ricercatori dell'Universit\u00e0 di Cincinnati e della Northwestern University hanno realizzato con il loro sistema \"Comp Cog AI\". Combinando l'intelligenza artificiale con la scienza del modo in cui la nostra mente elabora le informazioni, hanno creato uno strumento in grado di identificare con precisione le persone che potrebbero soffrire di ansia. Lo studio, pubblicato su Mental Health Research, ha coinvolto oltre 3.000 partecipanti provenienti da tutti gli Stati Uniti. Ciascuna persona ha valutato una serie di immagini lievemente emotive tratte dall'International Affective Picture System (IAPS) e ha valutato l'ansia.<\/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\/it\/2024\/06\/ai-system-can-predict-how-anxious-you-are-from-reactions-to-photos\/\" \/>\n<meta property=\"og:locale\" content=\"it_IT\" \/>\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\/it\/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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