AIMC Topic: Psychiatry

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Artificial Intelligence in mental health and the biases of language based models.

PloS one
BACKGROUND: The rapid integration of Artificial Intelligence (AI) into the healthcare field has occurred with little communication between computer scientists and doctors. The impact of AI on health outcomes and inequalities calls for health professi...

Digital Gaming Interventions in Psychiatry: Evidence, Applications and Challenges.

Psychiatry research
Human evolution has regularly intersected with technology. Digitalization of various services has brought a paradigm shift in consumerism. Treading this path, mental health practice has gradually moved to Digital Mental Health Interventions (DMHI), t...

Deep learning for the prediction of treatment response in depression.

Journal of affective disorders
BACKGROUND: Mood disorders are characterized by heterogeneity in severity, symptoms and treatment response. The possibility of selecting the correct therapy on the basis of patient-specific biomarker may be a considerable step towards personalized ps...

Machine learning for psychiatry: getting doctors at the black box?

Molecular psychiatry
Recent developments in the field of machine learning have spurred high hopes for diagnostic support for psychiatric patients based on brain MRI. But while technical advances are undoubtedly remarkable, the current trajectory of mostly proof-of-concep...

Classification of Depression Through Resting-State Electroencephalogram as a Novel Practice in Psychiatry: Review.

Journal of medical Internet research
BACKGROUND: Machine learning applications in health care have increased considerably in the recent past, and this review focuses on an important application in psychiatry related to the detection of depression. Since the advent of computational psych...

[Big Data, AI and Machine Learning for Precision Psychiatry: How are they changing the clinical practice?].

Fortschritte der Neurologie-Psychiatrie
Currently, we are witnessing an increasing interest in predictive models and personalized diagnosis and treatment choice in psychiatric research. Against this background, the emerging field of Precision Psychiatry is trying to establish precise diagn...

Precision psychiatry in clinical practice.

International journal of psychiatry in clinical practice
The treatment of depression represents a major challenge for healthcare systems and choosing among the many available drugs without objective guidance criteria is an error-prone process. Recently, pharmacogenetic biomarkers entered in prescribing gui...

Deep learning for small and big data in psychiatry.

Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology
Psychiatry today must gain a better understanding of the common and distinct pathophysiological mechanisms underlying psychiatric disorders in order to deliver more effective, person-tailored treatments. To this end, it appears that the analysis of '...

Computing schizophrenia: ethical challenges for machine learning in psychiatry.

Psychological medicine
Recent advances in machine learning (ML) promise far-reaching improvements across medical care, not least within psychiatry. While to date no psychiatric application of ML constitutes standard clinical practice, it seems crucial to get ahead of these...

The compatibility of theoretical frameworks with machine learning analyses in psychological research.

Current opinion in psychology
Supervised machine learning has been increasingly used in psychology and psychiatry research. Machine learning offers an important advantage over traditional statistical analyses: statistical model training in example data to enhance predictions in e...