AIMC Topic: Hallucinations
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Multi-dimensional predictions of psychotic symptoms via machine learning.
Human brain mapping
Sep 1, 2020
The diagnostic criteria for schizophrenia comprise a diverse range of heterogeneous symptoms. As a result, individuals each present a distinct set of symptoms despite having the same overall diagnosis. Whilst previous machine learning studies have pr...
Predominant polarity classification and associated clinical variables in bipolar disorder: A machine learning approach.
Journal of affective disorders
Nov 6, 2018
BACKGROUND: Bipolar disorder (BD) is a severe psychiatric disorder characterized by periodic episodes of manic and depressive symptomatology. Predominant polarity (PP) appears to be an important specifier of BD. The present study employed machine lea...
Substance-Related Disorders
Area Under Curve
Alcoholism
Tobacco Use Disorder
Cohort Studies
ROC Curve
Age Factors
Demography
Feeding and Eating Disorders
Hallucinations
Delusions
Female
Hospitalization
Adult
Cross-Sectional Studies
Male
Middle Aged
Bipolar Disorder
Humans
Machine Learning
Algorithms
Prediction of activation patterns preceding hallucinations in patients with schizophrenia using machine learning with structured sparsity.
Human brain mapping
Jan 16, 2018
Despite significant progress in the field, the detection of fMRI signal changes during hallucinatory events remains difficult and time-consuming. This article first proposes a machine-learning algorithm to automatically identify resting-state fMRI pe...
Discrimination of schizophrenia auditory hallucinators by machine learning of resting-state functional MRI.
International journal of neural systems
Jan 19, 2015
Auditory hallucinations (AH) are a symptom that is most often associated with schizophrenia, but patients with other neuropsychiatric conditions, and even a small percentage of healthy individuals, may also experience AH. Elucidating the neural mecha...
Predictors of schizophrenia spectrum disorders in early-onset first episodes of psychosis: a support vector machine model.
European child & adolescent psychiatry
Aug 11, 2014
Identifying early-onset schizophrenia spectrum disorders (SSD) at a very early stage remains challenging. To assess the diagnostic predictive value of multiple types of data at the emergence of early-onset first-episode psychosis (FEP), various suppo...
Psychological First Aid by AI: Proof-of-Concept and Comparative Performance of ChatGPT-4 and Gemini in Different Disaster Scenarios.
Journal of clinical psychology
Aug 1, 2025
OBJECTIVE: This study aimed to evaluate the performance and proof-of-concept of psychological first aid (PFA) provided by two AI chatbots, ChatGPT-4 and Gemini.
A Case of Artificial Intelligence Chatbot Hallucination.
JAMA otolaryngology-- head & neck surgery
Jun 1, 2024
Beware of Artificial Intelligence hallucinations or should we call confabulation?
Acta orthopaedica et traumatologica turcica
Jan 1, 2024
False Responses From Artificial Intelligence Models Are Not Hallucinations.
Schizophrenia bulletin
Sep 7, 2023
Evaluation and Comparison of Ophthalmic Scientific Abstracts and References by Current Artificial Intelligence Chatbots.
JAMA ophthalmology
Sep 1, 2023
IMPORTANCE: Language-learning model-based artificial intelligence (AI) chatbots are growing in popularity and have significant implications for both patient education and academia. Drawbacks of using AI chatbots in generating scientific abstracts and...
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