AIMC Topic: Psychotic Disorders
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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...
A natural language processing approach for identifying temporal disease onset information from mental healthcare text.
Scientific reports
Jan 12, 2021
Receiving timely and appropriate treatment is crucial for better health outcomes, and research on the contribution of specific variables is essential. In the mental health domain, an important research variable is the date of psychosis symptom onset,...
Predicting self-harm within six months after initial presentation to youth mental health services: A machine learning study.
PloS one
Dec 31, 2020
BACKGROUND: A priority for health services is to reduce self-harm in young people. Predicting self-harm is challenging due to their rarity and complexity, however this does not preclude the utility of prediction models to improve decision-making rega...
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...
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