Psychiatry

[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...

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

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

[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...

[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...

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...

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,...

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...

Predicting the 9-year course of mood and anxiety disorders with automated machine learning: A comparison between auto-sklearn, naïve Bayes classifier, and traditional logistic regression.

BACKGROUND: Predicting the onset and course of mood and anxiety disorders is of clinical importance ...

Patients' Preferences for Artificial Intelligence Applications Versus Clinicians in Disease Diagnosis During the SARS-CoV-2 Pandemic in China: Discrete Choice Experiment.

BACKGROUND: Misdiagnosis, arbitrary charges, annoying queues, and clinic waiting times among others ...

Convolutional Neural Network-Based Deep Learning Model for Predicting Differential Suicidality in Depressive Patients Using Brain Generalized q-Sampling Imaging.

OBJECTIVE: Suicide is a priority health problem. Suicide assessment depends on imperfect clinician a...

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...

Barriers and facilitators to the implementation of social robots for older adults and people with dementia: a scoping review protocol.

BACKGROUND: Psychosocial health issues such as depression and social isolation are an important caus...

Pattern classification as decision support tool in antipsychotic treatment algorithms.

Pattern classification aims to establish a new approach in personalized treatment. The scope is to t...

Using weak supervision and deep learning to classify clinical notes for identification of current suicidal ideation.

Mental health concerns, such as suicidal thoughts, are frequently documented by providers in clinica...

Use of a tele-operated robot to increase sociability in individuals with autism spectrum disorder who display Hikikomori.