AIMC Topic: Psychotic Disorders
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Machine Learning and Non-Affective Psychosis: Identification, Differential Diagnosis, and Treatment.
Current psychiatry reports
Nov 18, 2022
PURPOSE OF REVIEW: This review will cover the most relevant findings on the use of machine learning (ML) techniques in the field of non-affective psychosis, by summarizing the studies published in the last three years focusing on illness detection an...
Identification of texture MRI brain abnormalities on first-episode psychosis and clinical high-risk subjects using explainable artificial intelligence.
Translational psychiatry
Nov 16, 2022
Structural MRI studies in first-episode psychosis and the clinical high-risk state have consistently shown volumetric abnormalities. Aim of the present study was to introduce radiomics texture features in identification of psychosis. Radiomics textur...
Data augmentation with Mixup: Enhancing performance of a functional neuroimaging-based prognostic deep learning classifier in recent onset psychosis.
NeuroImage. Clinical
Sep 29, 2022
Although deep learning holds great promise as a prognostic tool in psychiatry, a limitation of the method is that it requires large training sample sizes to achieve replicable accuracy. This is problematic for fMRI datasets as they are typically smal...
Natural Language Processing markers in first episode psychosis and people at clinical high-risk.
Translational psychiatry
Dec 13, 2021
Recent work has suggested that disorganised speech might be a powerful predictor of later psychotic illness in clinical high risk subjects. To that end, several automated measures to quantify disorganisation of transcribed speech have been proposed. ...
Network analysis of trauma in patients with early-stage psychosis.
Scientific reports
Nov 23, 2021
Childhood trauma (ChT) is a risk factor for psychosis. Negative lifestyle factors such as rumination, negative schemas, and poor diet and exercise are common in psychosis. The present study aimed to perform a network analysis of interactions between ...
Causal pathways to social and occupational functioning in the first episode of schizophrenia: uncovering unmet treatment needs.
Psychological medicine
Oct 8, 2021
BACKGROUND: We aimed to identify unmet treatment needs for improving social and occupational functioning in early schizophrenia using a data-driven causal discovery analysis.
Predicting subclinical psychotic-like experiences on a continuum using machine learning.
NeuroImage
Jul 22, 2021
Previous studies applying machine learning methods to psychosis have primarily been concerned with the binary classification of chronic schizophrenia patients and healthy controls. The aim of this study was to use electroencephalographic (EEG) data a...
Deep learning based automatic diagnosis of first-episode psychosis, bipolar disorder and healthy controls.
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Feb 25, 2021
Neuroimaging data driven machine learning based predictive modeling and pattern recognition has been attracted strongly attention in biomedical sciences. Machine learning based diagnosis techniques are widely applied in diagnosis of neurological dise...
Pattern classification as decision support tool in antipsychotic treatment algorithms.
Experimental neurology
Feb 4, 2021
Pattern classification aims to establish a new approach in personalized treatment. The scope is to tailor treatment on individual characteristics during all phases of care including prevention, diagnosis, treatment, and clinical outcome. In psychotic...
Schizotypy in Parkinson's disease predicts dopamine-associated psychosis.
Scientific reports
Jan 12, 2021
Psychosis is the most common neuropsychiatric side-effect of dopaminergic therapy in Parkinson's disease (PD). It is still unknown which factors determine individual proneness to psychotic symptoms. Schizotypy is a multifaceted personality trait rela...
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