AIMC Topic: Psychotic Disorders
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A Pilot Analysis Investigating the Use of AI in Malingering.
The journal of the American Academy of Psychiatry and the Law
Jun 10, 2025
Generative artificial intelligence (AI), with its increasing ubiquity and power, will likely transform forensic psychiatry, sparking both advances and new challenges for the field. A possible consequence of the technology is that it will be used to a...
Personalized prediction of negative affect in individuals with serious mental illness followed using long-term multimodal mobile phenotyping.
Translational psychiatry
May 19, 2025
Heightened negative affect is a core feature of serious mental illness. Over 90% of American adults own a smartphone, equipped with an array of sensors which can continuously and unobtrusively measure behaviors (e.g., activity levels, location, and p...
Eye Movement Characteristics for Predicting a Transition to Psychosis: Longitudinal Changes and Implications.
Schizophrenia bulletin
Mar 14, 2025
BACKGROUND AND HYPOTHESIS: Substantive inquiry into the predictive power of eye movement (EM) features for clinical high-risk (CHR) conversion and their longitudinal trajectories is currently sparse. This study aimed to investigate the efficiency of ...
Deconstructing Cognitive Impairment in Psychosis With a Machine Learning Approach.
JAMA psychiatry
Jan 1, 2025
IMPORTANCE: Cognitive functioning is associated with various factors, such as age, sex, education, and childhood adversity, and is impaired in people with psychosis. In addition to specific effects of the disorder, cognitive impairments may reflect a...
False Responses From Artificial Intelligence Models Are Not Hallucinations.
Schizophrenia bulletin
Sep 7, 2023
A Deep Learning Approach for Psychosis Spectrum Label Noise Detection from Multimodal Neuroimaging Data.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2023
Understanding the structural and functional mechanisms of the brain is challenging for mood and mental disorders. Many neuroimaging techniques are widely used to reveal hidden patterns from different brain imaging modalities. However, these findings ...
Fingerprints as Predictors of Schizophrenia: A Deep Learning Study.
Schizophrenia bulletin
May 3, 2023
BACKGROUND AND HYPOTHESIS: The existing developmental bond between fingerprint generation and growth of the central nervous system points to a potential use of fingerprints as risk markers in schizophrenia. However, the high complexity of fingerprint...
Natural Language Processing and Psychosis: On the Need for Comprehensive Psychometric Evaluation.
Schizophrenia bulletin
Sep 1, 2022
BACKGROUND AND HYPOTHESIS: Despite decades of "proof of concept" findings supporting the use of Natural Language Processing (NLP) in psychosis research, clinical implementation has been slow. One obstacle reflects the lack of comprehensive psychometr...
Machine Learning Identifies Digital Phenotyping Measures Most Relevant to Negative Symptoms in Psychotic Disorders: Implications for Clinical Trials.
Schizophrenia bulletin
Mar 1, 2022
BACKGROUND: Digital phenotyping has been proposed as a novel assessment tool for clinical trials targeting negative symptoms in psychotic disorders (PDs). However, it is unclear which digital phenotyping measurements are most appropriate for this pur...
Prediction of Early Symptom Remission in Two Independent Samples of First-Episode Psychosis Patients Using Machine Learning.
Schizophrenia bulletin
Jan 21, 2022
BACKGROUND: Validated clinical prediction models of short-term remission in psychosis are lacking. Our aim was to develop a clinical prediction model aimed at predicting 4-6-week remission following a first episode of psychosis.
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