Frontiers | AI-Supported Learning and Clinical Innovation in Psychiatry and Medicine

About this Research Topic

This Research Topic is currently accepting articles, but is closing soon.

1. Check author guidelines

Background

The integration of artificial intelligence (AI) into psychiatry and medicine has transformed how clinicians learn, teach, and make decisions. This Research Topic aims to examine how AI-supported systems can enhance educational processes and clinical innovation in mental health and broader medical fields. We seek to bring together interdisciplinary contributions that address both technological and human aspects—how clinicians, educators, and researchers can effectively use AI to improve outcomes. The goal is to identify opportunities and boundaries of AI-based tools in psychiatry and medicine, define ethical and methodological standards, and stimulate international dialogue on responsible and effective AI implementation in healthcare.

Digital transformation in healthcare has accelerated rapidly, but psychiatry and medical education still face challenges in adapting to AI technologies. Many clinicians and educators remain cautious about algorithmic support, especially regarding interpretation, ethical use, and patient safety. Understanding how AI systems contribute to diagnostic accuracy, personalized learning, and clinical decision-making is now essential. This Research Topic will provide a platform for exploring both empirical findings and theoretical perspectives on how AI is reshaping knowledge transfer, competence development, and patient care in psychiatry and general medicine.

We welcome original research, reviews, perspectives, and conceptual papers that explore AI-supported approaches in psychiatric and medical education, diagnostics, and treatment planning. Potential themes include the following, but not limited to:

• AI-based decision support and clinical reasoning

• Machine learning applications in psychiatry and neurodevelopmental disorders

• Digital tools in medical and psychiatric training

• Ethical, cultural, and data privacy implications of AI in healthcare

• Comparative analyses between traditional and AI-enhanced learning or practice models

Generative AI tools (e.g., ChatGPT, DALL·E) are excluded from this Research Topic. Authors are encouraged to highlight practical applications, challenges, and multidisciplinary collaborations that foster innovation and responsibility in AI-driven psychiatry and medicine.

Article types and fees

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

Brief Research Report
Case Report
Clinical Trial
Community Case Study
Curriculum, Instruction, and Pedagogy
Data Report
Editorial
FAIR² Data
General Commentary

Articles that are accepted for publication by our external editors following rigorous peer review incur a publishing fee charged to Authors, institutions, or funders.

Keywords: Artificial intelligence, Digital psychiatry, Medical education, Clinical innovation, Ethical implications, Diagnostic support

Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.