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Diagnostic and Statistical Manual of Mental Disorders (DSM)01:27

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The Diagnostic and Statistical Manual of Mental Disorders (DSM) serves as the primary classification system for mental health disorders, providing standardized diagnostic criteria for clinicians and researchers. First published by the American Psychiatric Association (APA) in 1952, the DSM has undergone several revisions to reflect evolving psychiatric understanding. The fifth edition, DSM-5, released in 2013, introduced key updates that expanded diagnostic categories and modified diagnostic...
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Digital psychiatry: concepts, framework, and implications.

Hairong Wu1, Ming D Li1

  • 1State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Zhejiang University School of Medicine, Hangzhou, China.

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Summary
This summary is machine-generated.

Digital psychiatry integrates clinical practices with AI to automate mental healthcare, aiming for faster, consistent results. This review proposes a framework for fully automated digital psychiatric clinics, leveraging advanced technologies like large-scale pre-trained models and virtual reality.

Keywords:
AGIChatGPTGMAILLMSdigital healthmental healthpsychiatryvirtual reality

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Area of Science:

  • Digital Psychiatry
  • Artificial Intelligence in Healthcare
  • Mental Health Technology

Background:

  • Digital psychiatry merges clinical psychiatric practices with intelligent digital approaches.
  • Current digital tools like smartphone apps, VR, and chatbots are foundational but limited.
  • Advances in large-scale pre-trained models (PTMs) and digital humans offer new possibilities.

Purpose of the Study:

  • To propose a framework for fully automating mental health practices through digital psychiatry.
  • To outline the development of a fully-automated digital psychiatric system.
  • To explore the potential for digital psychiatric clinics.

Main Methods:

  • Review of technical developments in digital psychiatry, including digital entities, medical knowledge, autonomous agents, and VR.
  • Introduction of clinical mental health issues relevant to digital systems.
  • Proposal of a framework for an AI-driven, fully-automated digital psychiatric system.

Main Results:

  • Identifies opportunities for practical clinical use through digital entities, medical domain knowledge, autonomous agents, and VR.
  • Outlines a system for fully automated mental health practices.
  • Discusses challenges and key issues for real-world implementation.

Conclusions:

  • Digital psychiatry offers a pathway to automate psychiatric clinical processes for improved efficiency and consistency.
  • A fully-automated digital psychiatric system is feasible with current AI technologies.
  • Successful implementation requires addressing patient, provider, and regulatory considerations.