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Introduction
Part I Scientific Considerations and Challenges: AI-augmented neuroimaging
AI analytics in brain cancer screening
AI analytics to detect pre-symptomatic dementia
AI analytics in schizophrenia
Wearables, mHealth and mental health monitoring
Prevention of mental disorders through social media
The brain health modeling initiative and the promise of AI
Assistive robotics for dementia and mild cognitive impairment
Telehealth and robotherapy in psychiatry
Robot-assisted neurorehabilitation
Brain-computer interfaces and AI-mediated neuromodulation
Part III . Ethical Legal and Social Implications: Mental Privacy
Algorithmic transparency Measurement bias and ethical bias
Discrimination and stigma
Informed Consent
Minimal risk
Fairness and Research Allocation
The black-box problem of medical AI
The transformation of therapeutic relationships
The role of IRBs
The ethics of automated medical decision-making
Accountability and Responsibility
Designing moral technologies for brain and mental health
AI and Human Beings: Philosophical and Ethical Perspectives
Part III Policy Perspectives: Current regulatory frameworks in North America
Gaps in existing regulations
Policy and law of AI in China
Deontology and best practices
Regulation of AI industry
AI in the developing world: a global justice perspective
Regulation of AI in Europe
Conclusion - Towards an ethical framework for AI in brain and mental health.

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