AIMC Topic: Psychiatry

Clear Filters Showing 91 to 100 of 132 articles

Machine Learning for Precision Psychiatry: Opportunities and Challenges.

Biological psychiatry. Cognitive neuroscience and neuroimaging
The nature of mental illness remains a conundrum. Traditional disease categories are increasingly suspected to misrepresent the causes underlying mental disturbance. Yet psychiatrists and investigators now have an unprecedented opportunity to benefit...

Teaching to See Behaviors-Using Machine Learning?

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

Problematic internet use (PIU): Associations with the impulsive-compulsive spectrum. An application of machine learning in psychiatry.

Journal of psychiatric research
Problematic internet use is common, functionally impairing, and in need of further study. Its relationship with obsessive-compulsive and impulsive disorders is unclear. Our objective was to evaluate whether problematic internet use can be predicted f...

Machine learning, statistical learning and the future of biological research in psychiatry.

Psychological medicine
Psychiatric research has entered the age of 'Big Data'. Datasets now routinely involve thousands of heterogeneous variables, including clinical, neuroimaging, genomic, proteomic, transcriptomic and other 'omic' measures. The analysis of these dataset...

Validation of a novel classification model of psychogenic nonepileptic seizures by video-EEG analysis and a machine learning approach.

Epilepsy & behavior : E&B
The aim of this study was to validate a novel classification for the diagnosis of PNESs. Fifty-five PNES video-EEG recordings were retrospectively analyzed by four epileptologists and one psychiatrist in a blind manner and classified into four distin...

[Towards an equipped psychiatry].

L'Encephale
The article by Moizard and Geoffroy highlights the importance of an integrated approach in psychiatry, emphasizing the need to move beyond the dichotomy between the somatic and the psychic. In their commentary, the authors advocated for precision psy...

Integrating Knowledge: The Power of Ontologies in Psychiatric Research and Clinical Informatics.

Biological psychiatry
Ontologies are structured frameworks for representing knowledge by systematically defining concepts, categories, and their relationships. While widely adopted in biomedicine, ontologies remain largely absent in mental health research and clinical car...

Virtual and Augmented Reality in Undergraduate Medical Education in Psychiatry: A Systematic Review.

The clinical teacher
BACKGROUND: Simulation is widely used in medical education in all specialties; in psychiatry, it usually relies on standardised patients played by actors. Virtual and augmented reality (VR and AR) have the potential to provide standardised and replic...

Assessing bias in AI-driven psychiatric recommendations: A comparative cross-sectional study of chatbot-classified and CANMAT 2023 guideline for adjunctive therapy in difficult-to-treat depression.

Psychiatry research
The integration of chatbots into psychiatry introduces a novel approach to support clinical decision-making, but biases in their recommendations pose significant concerns. This study investigates potential biases in chatbot-generated recommendations ...