This paper is in the following e-collection/theme issue:

Artificial Intelligence (1323) Infodemiology and Infoveillance (1329) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1029) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1618) Eating Disorders (75) Validity, Reliability, and Bias (91)

Published on in Vol 25 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/45184, first published .
Gender Bias When Using Artificial Intelligence to Assess Anorexia Nervosa on Social Media: Data-Driven Study

Gender Bias When Using Artificial Intelligence to Assess Anorexia Nervosa on Social Media: Data-Driven Study

Gender Bias When Using Artificial Intelligence to Assess Anorexia Nervosa on Social Media: Data-Driven Study

Authors of this article:

David Solans Noguero1, 2 Author Orcid Image ;   Diana Ramírez-Cifuentes2, 3 Author Orcid Image ;   Esteban Andrés Ríssola4 Author Orcid Image ;   Ana Freire5 Author Orcid Image
Article Authors Cited by (7) Tweetations (14) Metrics

Journals

  1. Cuzzolaro M. Artificial intelligence and eating disorders: a commentary. Eating and Weight Disorders - Studies on Anorexia, Bulimia and Obesity 2023;28(1) View
  2. Khoo L, Lim M, Chong C, McNaney R. Machine Learning for Multimodal Mental Health Detection: A Systematic Review of Passive Sensing Approaches. Sensors 2024;24(2):348 View
  3. Norris M, Obeid N, El‐Emam K. Examining the role of artificial intelligence to advance knowledge and address barriers to research in eating disorders. International Journal of Eating Disorders 2024;57(6):1357 View
  4. Kim Y, Serpedin A, Periyakoil P, German D, Rameau A. Sociodemographic reporting in videomics research: a review of practices in otolaryngology - head and neck surgery. European Archives of Oto-Rhino-Laryngology 2024 View
  5. Cabanillas Silva P, Sun H, Rodriguez-Brazzarola P, Rezk M, Zhang X, Fliegenschmidt J, Hulde N, von Dossow V, Meesseman L, Depraetere K, Szymanowsky R, Stieg J, Dahlweid F. Evaluating gender bias in ML-based clinical risk prediction models: A study on multiple use cases at different hospitals. Journal of Biomedical Informatics 2024;157:104692 View
  6. Kanbar L, Mishra A, Osborn A, Cifuentes A, Combs J, Sorter M, Barzman D, Dexheimer J. Investigation of bias in the automated assessment of school violence. Journal of Biomedical Informatics 2024;157:104709 View

Books/Policy Documents

  1. Rubeis G. Ethics of Medical AI. View