Artificial Intelligence and Social Media for the Detection of Eating Disorders.

IF 4.7 2区 医学 Q1 NUTRITION & DIETETICS
Jinbo He, Feng Ji
{"title":"Artificial Intelligence and Social Media for the Detection of Eating Disorders.","authors":"Jinbo He, Feng Ji","doi":"10.1002/eat.24438","DOIUrl":null,"url":null,"abstract":"<p><p>Artificial intelligence (AI) has been increasingly recognized for its potential in mental health management, including detecting, preventing, and treating eating disorders (EDs). Linardon et al. investigated current practices and perspectives on AI in ED treatment from professionals and community participants. While their work provides valuable insights into AI's role in ED management in the treatment phase, the applications of AI at earlier stages, particularly for case detection, and perspectives of key groups involved in this early-stage implementation (e.g., health professionals and individuals with or at risk of EDs) remain underexplored. Given the large volume of multimodal data available on social media platforms, together with their widespread use and accessibility, the integration of AI and social media provides an ideal opportunity for conducting large-scale, population-based detection for EDs. Thus, in this commentary, we discuss AI's potential to leverage social media data for case detection, highlight related ethical considerations (e.g., bias and data privacy), and propose future research directions.</p>","PeriodicalId":51067,"journal":{"name":"International Journal of Eating Disorders","volume":" ","pages":""},"PeriodicalIF":4.7000,"publicationDate":"2025-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Eating Disorders","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1002/eat.24438","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"NUTRITION & DIETETICS","Score":null,"Total":0}
引用次数: 0

Abstract

Artificial intelligence (AI) has been increasingly recognized for its potential in mental health management, including detecting, preventing, and treating eating disorders (EDs). Linardon et al. investigated current practices and perspectives on AI in ED treatment from professionals and community participants. While their work provides valuable insights into AI's role in ED management in the treatment phase, the applications of AI at earlier stages, particularly for case detection, and perspectives of key groups involved in this early-stage implementation (e.g., health professionals and individuals with or at risk of EDs) remain underexplored. Given the large volume of multimodal data available on social media platforms, together with their widespread use and accessibility, the integration of AI and social media provides an ideal opportunity for conducting large-scale, population-based detection for EDs. Thus, in this commentary, we discuss AI's potential to leverage social media data for case detection, highlight related ethical considerations (e.g., bias and data privacy), and propose future research directions.

求助全文
约1分钟内获得全文 求助全文
来源期刊
CiteScore
10.00
自引率
12.70%
发文量
204
审稿时长
4-8 weeks
期刊介绍: Articles featured in the journal describe state-of-the-art scientific research on theory, methodology, etiology, clinical practice, and policy related to eating disorders, as well as contributions that facilitate scholarly critique and discussion of science and practice in the field. Theoretical and empirical work on obesity or healthy eating falls within the journal’s scope inasmuch as it facilitates the advancement of efforts to describe and understand, prevent, or treat eating disorders. IJED welcomes submissions from all regions of the world and representing all levels of inquiry (including basic science, clinical trials, implementation research, and dissemination studies), and across a full range of scientific methods, disciplines, and approaches.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信