Feng Liu , Qianqian Ju , Qijian Zheng , Yujia Peng
{"title":"人工智能在心理健康中的应用:人工智能技术在压力检测和复原力建设干预方面带来的创新","authors":"Feng Liu , Qianqian Ju , Qijian Zheng , Yujia Peng","doi":"10.1016/j.cobeha.2024.101452","DOIUrl":null,"url":null,"abstract":"<div><div>The last few decades have witnessed a revolution in the field of mental health, brought about by state-of-the-art techniques of artificial intelligence (AI). Here, we review the evidence for the systematic application of AI for the detection and intervention of stress-related mental health problems. We first explore the potential application of AI in stress detection and screening through advanced computational techniques of machine learning algorithms that analyze biomarkers of stress and anxiety. Building on the accurate detection of mental health problems, we further review the evidence for AI-based stress interventions and propose the promising prospect of applying decoded neurofeedback as a personalized resilience-building intervention. Together, the current review assesses the effectiveness and major challenges of AI technologies in real-world applications and demonstrates the transforming impact of AI on the field of mental health.</div></div>","PeriodicalId":56191,"journal":{"name":"Current Opinion in Behavioral Sciences","volume":"60 ","pages":"Article 101452"},"PeriodicalIF":4.9000,"publicationDate":"2024-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Artificial intelligence in mental health: innovations brought by artificial intelligence techniques in stress detection and interventions of building resilience\",\"authors\":\"Feng Liu , Qianqian Ju , Qijian Zheng , Yujia Peng\",\"doi\":\"10.1016/j.cobeha.2024.101452\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>The last few decades have witnessed a revolution in the field of mental health, brought about by state-of-the-art techniques of artificial intelligence (AI). Here, we review the evidence for the systematic application of AI for the detection and intervention of stress-related mental health problems. We first explore the potential application of AI in stress detection and screening through advanced computational techniques of machine learning algorithms that analyze biomarkers of stress and anxiety. Building on the accurate detection of mental health problems, we further review the evidence for AI-based stress interventions and propose the promising prospect of applying decoded neurofeedback as a personalized resilience-building intervention. Together, the current review assesses the effectiveness and major challenges of AI technologies in real-world applications and demonstrates the transforming impact of AI on the field of mental health.</div></div>\",\"PeriodicalId\":56191,\"journal\":{\"name\":\"Current Opinion in Behavioral Sciences\",\"volume\":\"60 \",\"pages\":\"Article 101452\"},\"PeriodicalIF\":4.9000,\"publicationDate\":\"2024-09-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Current Opinion in Behavioral Sciences\",\"FirstCategoryId\":\"102\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2352154624001037\",\"RegionNum\":2,\"RegionCategory\":\"心理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"BEHAVIORAL SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Current Opinion in Behavioral Sciences","FirstCategoryId":"102","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2352154624001037","RegionNum":2,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BEHAVIORAL SCIENCES","Score":null,"Total":0}
Artificial intelligence in mental health: innovations brought by artificial intelligence techniques in stress detection and interventions of building resilience
The last few decades have witnessed a revolution in the field of mental health, brought about by state-of-the-art techniques of artificial intelligence (AI). Here, we review the evidence for the systematic application of AI for the detection and intervention of stress-related mental health problems. We first explore the potential application of AI in stress detection and screening through advanced computational techniques of machine learning algorithms that analyze biomarkers of stress and anxiety. Building on the accurate detection of mental health problems, we further review the evidence for AI-based stress interventions and propose the promising prospect of applying decoded neurofeedback as a personalized resilience-building intervention. Together, the current review assesses the effectiveness and major challenges of AI technologies in real-world applications and demonstrates the transforming impact of AI on the field of mental health.
期刊介绍:
Current Opinion in Behavioral Sciences is a systematic, integrative review journal that provides a unique and educational platform for updates on the expanding volume of information published in the field of behavioral sciences.