{"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\/de\/2024\/06\/ai-system-can-predict-how-anxious-you-are-from-reactions-to-photos\/","title":{"rendered":"KI-System kann anhand der Reaktionen auf Fotos vorhersagen, wie \u00e4ngstlich Sie sind"},"content":{"rendered":"

Stellen Sie sich vor, Sie k\u00f6nnten das Angstniveau einer Person vorhersagen, indem Sie sie einfach ein paar Bilder bewerten und einige einfache Fragen beantworten lassen. <\/strong><\/p>\n

Genau das haben Forscher der University of Cincinnati und der Northwestern University mit ihrem \"Comp Cog AI\"-System erreicht.\u00a0<\/span><\/p>\n

Durch die Kombination von k\u00fcnstlicher Intelligenz mit der Wissenschaft, wie unser Gehirn Informationen verarbeitet, haben sie ein Tool entwickelt, das Menschen, die mit \u00c4ngsten zu k\u00e4mpfen haben k\u00f6nnten, genau identifizieren kann.\u00a0<\/span><\/p>\n

Die <\/span>Studie<\/span><\/a>die in der Zeitschrift Mental Health Research ver\u00f6ffentlicht wurde, waren \u00fcber 3 000 Teilnehmer aus den gesamten USA beteiligt. <\/span><\/p>\n

Jede Person bewertete eine Reihe von leicht emotionalen Bildern aus dem International Affective Picture System (IAPS) und gab grundlegende Informationen \u00fcber sich selbst an, wie z. B. Alter und wahrgenommene Einsamkeit.\u00a0<\/span><\/p>\n

IAPS wurde vom Center for the Study of Emotion and Attention an der Universit\u00e4t von Florida entwickelt. Es bietet eine standardisierte Reihe von Fotos, die nach ihrem emotionalen Gehalt in Bezug auf Valenz (Angenehmheit), Erregung (Intensit\u00e4t) und Dominanz (Kontrolle) bewertet werden.<\/p>\n

\"Ai-Emotionen\"
Ein Beispiel f\u00fcr ein Bild aus dem International Affective Picture System (IAPS). Quelle: Mental Health Research.<\/figcaption><\/figure>\n

Das KI-System analysierte dann diese Daten und suchte nach Mustern in der Art und Weise, wie die Menschen auf die Bilder reagierten und wie diese Reaktionen mit ihren Angstzust\u00e4nden zusammenhingen.\u00a0<\/span><\/p>\n

Nach dem Training war das KI-System von Comp Cog in der Lage, Angstzust\u00e4nde mit einer Genauigkeit von bis zu 81% vorherzusagen. Dies l\u00e4sst auf eine Zukunft hoffen, in der psychische Probleme mit Hilfe von leichten Selbstbedienungssystemen erkannt werden k\u00f6nnen.\u00a0<\/span><\/p>\n

Wie die Hauptautorin Sumra Bari <\/span>erkl\u00e4rt<\/span><\/a>Wir haben minimale Rechenressourcen und einen kleinen Satz von Variablen verwendet, um Angstzust\u00e4nde vorherzusagen. Ein wichtiger Teil dieser Variablen quantifiziert Prozesse, die f\u00fcr die Beurteilung wichtig sind.<\/span><\/p>\n

Mehr \u00fcber die Studie<\/h2>\n

Hier erfahren Sie mehr dar\u00fcber, wie die Studie funktioniert hat:<\/p>\n

    \n
  1. Datenerhebung<\/b>: Die Teilnehmer bewerteten 48 leicht emotionale Bilder aus IAPS mit einer Skala von -3 (sehr unangenehm) bis +3 (sehr angenehm). Au\u00dferdem beantworteten sie Fragen zu ihrem Alter, ihrer wahrgenommenen Einsamkeit und zu demografischen Informationen.<\/span><\/li>\n
  2. Merkmalsextraktion<\/b>: Das KI-System extrahierte 15 Schl\u00fcsselvariablen aus den Bildbewertungsdaten, z. B. Verlustaversion, Risikoaversion und Konsistenz der Belohnungsaversion. Diese Variablen quantifizieren Verzerrungen bei der Beurteilung von Belohnungen\/Abneigungen und wurden mit Gehirnsystemen in Verbindung gebracht, die sowohl bei der Beurteilung als auch bei \u00c4ngsten eine Rolle spielen.<\/span><\/li>\n
  3. KI-Training und Vorhersage<\/b>: Die Forscher verwendeten Random-Forest- und ausgewogene Random-Forest-Algorithmen f\u00fcr maschinelles Lernen, um das KI-System auf einer Teilmenge der Daten zu trainieren. Die KI nutzte die Urteilsvariablen und Kontextfaktoren, um das Angstniveau jedes Teilnehmers vorherzusagen, das mit dem State-Trait Anxiety Inventory (STAI) gemessen wurde.<\/span><\/li>\n
  4. Modellbewertung und -interpretation<\/b>: Das trainierte KI-System wurde an den verbleibenden Daten getestet, um seine Genauigkeit, Sensitivit\u00e4t und Spezifit\u00e4t bei der Vorhersage von Angstzust\u00e4nden zu bewerten. Die Forscher f\u00fchrten auch Mediations- und Moderationsanalysen durch, um zu verstehen, wie die Urteilsvariablen und Kontextfaktoren bei der Modellierung der Angst zusammenwirken.<\/span><\/li>\n<\/ol>\n

    Die vier wichtigsten Pr\u00e4diktoren - Alter, Einsamkeit, Haushaltseinkommen und Besch\u00e4ftigungsstatus - trugen 29-31% zur Vorhersagekraft des Modells bei, w\u00e4hrend die 15 Urteilsvariablen zusammen 55-61% beitrugen.<\/span><\/p>\n

    Mitautor Aggelos Katsaggelos hob die Bedeutung des Ansatzes der Studie hervor: \"Die Verwendung einer Bildbewertungsaufgabe mit Kontextvariablen, die das Urteilsverm\u00f6gen beeinflussen, mag einfach erscheinen, aber das Verst\u00e4ndnis von Pr\u00e4ferenzmustern erm\u00f6glicht es uns, die kritischen Komponenten f\u00fcr eine gro\u00dfe Anzahl von Verhaltensweisen aufzudecken\".<\/span><\/p>\n

    Die Forscher wollen die KI-Technologie von Comp Cog zu einer benutzerfreundlichen App f\u00fcr Gesundheitsdienstleister, Krankenh\u00e4user und sogar das Milit\u00e4r weiterentwickeln, um Personen mit hohem Risiko f\u00fcr Angstzust\u00e4nde schnell zu identifizieren.\u00a0<\/span><\/p>\n

    Bari merkt an: \"Die Bildbewertungsaufgabe kann verwendet werden, um t\u00e4gliche und unvoreingenommene Momentaufnahmen des psychischen Gesundheitszustands einer Person zu erstellen, ohne direkte Fragen zu stellen, die negative oder beunruhigende Gef\u00fchle ausl\u00f6sen k\u00f6nnten.\"\u00a0<\/span><\/p>\n

    Fr\u00fchere Forschungen nutzten KI, um bei der Diagnose von Schizophrenie helfen<\/a>und es wurden Instrumente entwickelt, um Menschen mit psychischen Erkrankungen eine KI-Therapie anzubieten. durch digitale Avatare<\/a>.\u00a0<\/span><\/p>","protected":false},"excerpt":{"rendered":"

    Stellen Sie sich vor, Sie k\u00f6nnten das Angstniveau einer Person vorhersagen, indem Sie sie einfach ein paar Bilder bewerten und einige einfache Fragen beantworten lassen. Genau das haben Forscher der University of Cincinnati und der Northwestern University mit ihrem System \"Comp Cog AI\" erreicht. Durch die Kombination von k\u00fcnstlicher Intelligenz mit der Wissenschaft, wie unser Gehirn Informationen verarbeitet, haben sie ein Instrument geschaffen, das Menschen, die mit Angstzust\u00e4nden zu k\u00e4mpfen haben, genau identifizieren kann. An der Studie, die in der Fachzeitschrift Mental Health Research ver\u00f6ffentlicht wurde, nahmen \u00fcber 3 000 Teilnehmer aus den USA teil. Jede Person bewertete eine Reihe von leicht emotionalen Bildern aus dem International Affective Picture System (IAPS) und<\/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\/de\/2024\/06\/ai-system-can-predict-how-anxious-you-are-from-reactions-to-photos\/\" \/>\n<meta property=\"og:locale\" content=\"de_DE\" \/>\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\/de\/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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