Psychiatry

Latest AI and machine learning research in psychiatry for healthcare professionals.

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Reducing negative emotions in children using social robots: systematic review.

BACKGROUND: For many children, visiting the hospital can lead to a state of increased anxiety. Socia...

Privacy-Preserving Deep Speaker Separation for Smartphone-Based Passive Speech Assessment.

Smartphones can be used to passively assess and monitor patients' speech impairments caused by ailm...

[Comments on Relationships with Artificial Emotional Intelligence - from "Here and Now" to "There and Then"].

The structure of relationships in the past, the present and the future is shaped by the idea of huma...

[Psychotherapy with an Autonomous Artifical Intelligence - Ethical Benefits and Challenges].

OBJECTIVE: This paper provides an overview of a range of ethical aspects involved in the use of auto...

[Brave New Psychiatry? Or: What Astray is Artificial Intelligence Leading Psychiatry?].

The article summarizes various publications on the application of "learning algorithms" and "artific...

[Diagnostics and Therapy 24/7? Artificial Intelligence as a Challenge and Opportunity in Psychiatry and Psychotherapy].

OBJECTIVE: The aim of the article is to enable a fundamental understanding of the potentials and req...

Machine Learning Assessment of Early Life Factors Predicting Suicide Attempt in Adolescence or Young Adulthood.

IMPORTANCE: Although longitudinal studies have reported associations between early life factors (ie,...

Machine learning and bioinformatic analysis of brain and blood mRNA profiles in major depressive disorder: A case-control study.

This study analyzed gene expression messenger RNA data, from cases with major depressive disorder (M...

Protein glycation - biomarkers of metabolic dysfunction and early-stage decline in health in the era of precision medicine.

Protein glycation provides a biomarker in widespread clinical use, glycated hemoglobin HbA (A1C). It...

Deep learning based automatic diagnosis of first-episode psychosis, bipolar disorder and healthy controls.

Neuroimaging data driven machine learning based predictive modeling and pattern recognition has been...

Patient journey through cases of depression from claims database using machine learning algorithms.

Health insurance and acute hospital-based claims have recently become available as real-world data a...

Paradoxical sensory reactivity induced by functional disconnection in a robot model of neurodevelopmental disorder.

Neurodevelopmental disorders are characterized by heterogeneous and non-specific nature of their cli...

Whole-brain modelling of resting state fMRI differentiates ADHD subtypes and facilitates stratified neuro-stimulation therapy.

Recent advances in non-linear computational and dynamical modelling have opened up the possibility t...

Resting-state functional network models for posttraumatic stress disorder.

Four recent articles were examined for their use of resting-state functional magnetic resonance imag...

Deep learning applications for the classification of psychiatric disorders using neuroimaging data: Systematic review and meta-analysis.

Deep learning (DL) methods have been increasingly applied to neuroimaging data to identify patients ...

Artificial Intelligence for Mental Health Care: Clinical Applications, Barriers, Facilitators, and Artificial Wisdom.

Artificial intelligence (AI) is increasingly employed in health care fields such as oncology, radiol...

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