AIMC Topic: Psychotic Disorders

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The risks of risk. Regulating the use of machine learning for psychosis prediction.

International journal of law and psychiatry Aug 17, 2019
Recent advances in Machine Learning (ML) have the potential to revolutionise psychosis prediction and psychiatric assessment. This article has two objectives. First, it clarifies which aspects of English Law are relevant in order to regulate the use ...
Psychiatry Risk Assessment Psychotic Disorders United Kingdom Humans Machine Learning Algorithms
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Identifying psychosis spectrum disorder from experience sampling data using machine learning approaches.

Schizophrenia research May 16, 2019
The ubiquity of smartphones opened up the possibility of widespread use of the Experience Sampling Method (ESM). The method is used to collect longitudinal data of participants' daily life experiences and is ideal to capture fluctuations in emotions ...
Emotions Principal Component Analysis Psychotic Disorders Monte Carlo Method Smartphone Logistic Models Support Vector Machine Humans Ecological Momentary Assessment Neural Networks, Computer Machine Learning Female Male Case-Control Studies ROC Curve
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Relative importance of symptoms, cognition, and other multilevel variables for psychiatric disease classifications by machine learning.

Psychiatry research Mar 29, 2019
This study used machine-learning algorithms to make unbiased estimates of the relative importance of various multilevel data for classifying cases with schizophrenia (n = 60), schizoaffective disorder (n = 19), bipolar disorder (n = 20), unipolar dep...
Machine Learning Female Adult Male Humans Schizophrenic Psychology Parents Cognition Schizophrenia Psychotic Disorders Middle Aged Depressive Disorder, Major Bipolar Disorder
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Predicting one-year outcome in first episode psychosis using machine learning.

PloS one Mar 7, 2019
BACKGROUND: Early illness course correlates with long-term outcome in psychosis. Accurate prediction could allow more focused intervention. Earlier intervention corresponds to significantly better symptomatic and functional outcomes. Our study object...
Glasgow Outcome Scale Adult Male Psychiatric Status Rating Scales Adolescent Psychotic Disorders Datasets as Topic Employment Models, Psychological Prognosis Female Educational Status Young Adult Humans Machine Learning Prospective Studies
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The Early Psychosis Screener for Internet (EPSI)-SR: Predicting 12 month psychotic conversion using machine learning.

Schizophrenia research Feb 15, 2019
INTRODUCTION: A faster and more accurate self-report screener for early psychosis is needed to promote early identification and intervention.
Risk Assessment Diagnosis, Computer-Assisted Support Vector Machine Predictive Value of Tests Humans Machine Learning Internet Psychotic Disorders Early Diagnosis
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Machine learning for predicting psychotic relapse at 2 years in schizophrenia in the national FACE-SZ cohort.

Progress in neuro-psychopharmacology & biological psychiatry Dec 12, 2018
BACKGROUND: Predicting psychotic relapse is one of the major challenges in the daily care of schizophrenia.
Humans Psychiatric Status Rating Scales Cohort Studies Adult Follow-Up Studies Sensitivity and Specificity Psychotic Disorders Machine Learning Schizophrenia Male Recurrence Prognosis Diagnosis, Computer-Assisted Schizophrenic Psychology Female Aggression
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Using fMRI and machine learning to predict symptom improvement following cognitive behavioural therapy for psychosis.

NeuroImage. Clinical Oct 10, 2018
Cognitive behavioural therapy for psychosis (CBTp) involves helping patients to understand and reframe threatening appraisals of their psychotic experiences to reduce distress and increase functioning. Whilst CBTp is effective for many, it is not eff...
Magnetic Resonance Imaging Schizophrenia Adult Psychotic Disorders Humans Cognitive Behavioral Therapy Male Machine Learning Middle Aged Female Treatment Outcome
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Is It Ethical to Use Prognostic Estimates from Machine Learning to Treat Psychosis?

AMA journal of ethics Sep 1, 2018
Machine learning is a method for predicting clinically relevant variables, such as opportunities for early intervention, potential treatment response, prognosis, and health outcomes. This commentary examines the following ethical questions about mach...
Humans Machine Learning Prognosis Treatment Outcome Psychotic Disorders Morals
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Reading the (functional) writing on the (structural) wall: Multimodal fusion of brain structure and function via a deep neural network based translation approach reveals novel impairments in schizophrenia.

NeuroImage Jul 25, 2018
This work presents a novel approach to finding linkage/association between multimodal brain imaging data, such as structural MRI (sMRI) and functional MRI (fMRI). Motivated by the machine translation domain, we employ a deep learning model, and consi...
Nerve Net Humans Female Adult Schizophrenia Middle Aged Male Psychotic Disorders Deep Learning Gray Matter Magnetic Resonance Imaging Connectome
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Machine learning improved classification of psychoses using clinical and biological stratification: Update from the bipolar-schizophrenia network for intermediate phenotypes (B-SNIP).

Schizophrenia research May 26, 2018
Diagnosis, Computer-Assisted Psychiatric Status Rating Scales Bipolar Disorder Magnetic Resonance Imaging Female Adult Humans Male Machine Learning Schizophrenia Phenotype Psychotic Disorders Pattern Recognition, Automated Neuropsychological Tests
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