ORIGINAL RESEARCH article
Front. Med.
Sec. Dermatology
Volume 12 - 2025 | doi: 10.3389/fmed.2025.1709891
This article is part of the Research TopicVitiligo: From Obscurity to Spotlight – Advancing Care with New Therapies and AIView all 12 articles
Prototype of a Multimodal AI System for Vitiligo Detection and Mental Health Monitoring
Provisionally accepted
- 1Universidad de Malaga, Málaga, Spain
- 2George Emil Palade University of Medicine, Pharmacy, Sciences and Technology of Târgu Mureş, Târgu Mures, Romania
Select one of your emails
You have multiple emails registered with Frontiers:
Notify me on publication
Please enter your email address:
If you already have an account, please login
You don't have a Frontiers account ? You can register here
Background: Vitiligo is a chronic autoimmune disorder with profound psychosocial implications. Methods: The paper propose a multimodal artificial intelligence (AI) framework that combines and integrates YOLOv11 for the detection of dermatological lesion and a BERT-based sentiment classifier for the monitoring of mental health, supported by questionnaire data sets (DLQI, RSE). Results: YOLOv11 achieved mAP = 98.8%, precision = 95.6%, recall = 97.0%; The mental health module uses a BERT-based sentiment classifier, fine-tuned in the GoEmotions corpus, reaching F1 = 0.83. A simulated fusion score that integrates the Dermatology Life Quality Index (DLQI) and Rosenberg Self-Esteem (RSE) scores, resulting in an area under the ROC curve (AUC) of 0.82 for the identification of high-risk patients. Conclusion: The implemented prototype establishes the feasibility of AI-assisted psychodermatology, allowing early diagnosis, emotional monitoring, and real-time alerting by physicians.
Keywords: Vitiligo, Autoimmune disorder, YOLOv11, artificial intelligence, sentiment analysis, Mental health monitoring, psychodermatology, personalized medicine
Received: 21 Sep 2025; Accepted: 13 Oct 2025.
Copyright: © 2025 Biró, Iantovics, Fekete and Gyula Laszlo. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Laszlo Barna Iantovics, barna.iantovics@umfst.ro
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.