REVIEW article
Front. Comput. Neurosci.
This article is part of the Research TopicReviews in: AI for clinical applications in computational neuroscienceView all articles
Toward Precision Medicine in Tourette Syndrome: A Perspective on AI-Driven Predictive Modeling and Personalized Care
Provisionally accepted
- Henan University of Traditional Chinese Medicine, Zhengzhou, China
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Abstract Tourette Syndrome (TS) is a complex neurodevelopmental disorder characterized by motor and vocal tics that significantly impair quality of life. Conventional diagnostic and therapeutic methods face challenges due to subjectivity, lack of personalization, and difficulties in prognostic prediction. Artificial Intelligence (AI) offers novel solutions, advancing TS management toward precision medicine. This article presents a conceptual framework for AI-driven technologies in TS, advocating for a paradigm shift from empirical treatment to precision medicine. We discuss key components including predictive model construction, personalized diagnosis, treatment strategies, and intelligent monitoring. Research indicates that the core value of AI in TS precision medicine lies in its predictiveness, individualization, and intelligence. Predictive models using multimodal data enable early identification and prognostic assessment. Furthermore, personalized approaches tailor diagnosis and treatment to individual patient characteristics, thereby improving outcomes. Intelligent systems enable automated monitoring and real-time adjustments, optimizing clinical workflows. Substantial clinical evidence demonstrates that AI-driven precision medicine improves diagnostic accuracy, optimizes treatments, and enhances patient prognosis. Despite this potential, challenges remain in data quality, algorithm interpretability, and clinical translation. Future efforts should focus on enhancing interdisciplinary collaboration, promoting standardization, and facilitating clinical adoption to deliver more precise, effective, and accessible care for TS patients.
Keywords: artificial intelligence, machine learning, personalized treatment, precision medicine, predictive models, Tourette Syndrome
Received: 20 Dec 2025; Accepted: 31 Jan 2026.
Copyright: © 2026 Zhao, Li, Hua, Li, Zhang and Wang. 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: Ruixing Li
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