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Psychiatry

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What do patients learn about psychotropic medications on the web? A natural language processing study.

Journal of affective disorders
BACKGROUND: Low rates of medication adherence remain a major challenge across psychiatry. In part, this likely reflects patient concerns about safety and adverse effects, accurate or otherwise. We therefore sought to characterize online information a...

Using machine learning to explain the heterogeneity of schizophrenia. Realizing the promise and avoiding the hype.

Schizophrenia research
Despite extensive research and prodigious advances in neuroscience, our comprehension of the nature of schizophrenia remains rudimentary. Our failure to make progress is attributed to the extreme heterogeneity of this condition, enormous complexity o...

The risks of risk. Regulating the use of machine learning for psychosis prediction.

International journal of law and psychiatry
Recent advances in Machine Learning (ML) have the potential to revolutionise psychosis prediction and psychiatric assessment. This article has two objectives. First, it clarifies which aspects of English Law are relevant in order to regulate the use ...

The Future of Digital Psychiatry.

Current psychiatry reports
PURPOSE OF REVIEW: Treatments in psychiatry have been rapidly changing over the last century, following the development of psychopharmacology and new research achievements. However, with advances in technology, the practice of psychiatry in the futur...

Machine learning and big data: Implications for disease modeling and therapeutic discovery in psychiatry.

Artificial intelligence in medicine
INTRODUCTION: Machine learning capability holds promise to inform disease models, the discovery and development of novel disease modifying therapeutics and prevention strategies in psychiatry. Herein, we provide an introduction on how machine learnin...

Computational approaches and machine learning for individual-level treatment predictions.

Psychopharmacology
RATIONALE: The impact of neuroscience-based approaches for psychiatry on pragmatic clinical decision-making has been limited. Although neuroscience has provided insights into basic mechanisms of neural function, these insights have not improved the a...

Your Robot Therapist Will See You Now: Ethical Implications of Embodied Artificial Intelligence in Psychiatry, Psychology, and Psychotherapy.

Journal of medical Internet research
BACKGROUND: Research in embodied artificial intelligence (AI) has increasing clinical relevance for therapeutic applications in mental health services. With innovations ranging from 'virtual psychotherapists' to social robots in dementia care and aut...

Deep neural networks in psychiatry.

Molecular psychiatry
Machine and deep learning methods, today's core of artificial intelligence, have been applied with increasing success and impact in many commercial and research settings. They are powerful tools for large scale data analysis, prediction and classific...

How to Prepare Prospective Psychiatrists in the Era of Artificial Intelligence.

Academic psychiatry : the journal of the American Association of Directors of Psychiatric Residency Training and the Association for Academic Psychiatry