Artificial Intelligence in Mental Health: Advances in Predictive Modeling, Intervention Strategies and Outcome Analysis
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".
Deadline for manuscript submissions: 20 August 2025 | Viewed by 203
Special Issue Editors
Interests: rehabilitation; balance; muscle; postural balance; stance; body equilibrium; gait; gait analysis; deep learning; motion capture; ethoprop
Interests: occupational therapy; mental health; mental illness; disability; rehabilitation; machine learning
Interests: artificial intelligence; intelligent image analytics; embedded systems; intelligent vehicles; smart manufacturing
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Special Issue Information
Dear Colleagues,
This Special Issue aims to explore the transformative potential of artificial intelligence (AI) in addressing the complex challenges of mental health. With the increasing availability of data and advancements in AI methodologies, this field has emerged as a critical area of innovation for improving the diagnosis, treatment, and management of mental illnesses.
We welcome original research articles, reviews, and case studies that highlight advances in AI-driven predictive modeling for the early detection and risk assessment of mental health conditions, novel intervention strategies leveraging AI to deliver personalized care, and outcome analysis tools that enhance the evaluation of therapeutic efficacy and patient progress. Topics of interest include, but are not limited to, the following:
- Development and validation of AI models for diagnosing and predicting mental health conditions.
- Applications of machine learning, natural language processing, and computer vision in mental health assessment and monitoring.
- AI-powered tools for designing and delivering personalized therapeutic interventions.
- Techniques for analyzing treatment outcomes and long-term patient well-being using AI.
This Special Issue provides an interdisciplinary platform for researchers, clinicians, and technologists to share insights and innovations at the intersection of AI and mental health. By bridging cutting-edge AI methodologies with clinical practice, we aim to advance mental health care toward greater precision, accessibility, and effectiveness.
Prof. Dr. Posen Lee
Dr. Chin-Hsuan Liu
Prof. Dr. Yen-Lin Chen
Guest Editors
Manuscript Submission Information
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Keywords
- artificial intelligence
- mental health
- predictive modeling
- personalized interventions
- outcome analysis
- machine learning
- natural language processing
- psychiatric diagnosis
- therapeutic innovation
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