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Schizophrenia

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Prediction of Early Symptom Remission in Two Independent Samples of First-Episode Psychosis Patients Using Machine Learning.

Schizophrenia bulletin
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.

Decision support system for the differentiation of schizophrenia and mood disorders using multiple deep learning models on wearable devices data.

Health informatics journal
In the modern world, with so much inherent stress, mental health disorders (MHDs) are becoming more common in every country around the globe, causing a significant burden on society and patients' families. MHDs come in many forms with various severit...

Multi-modal deep learning of functional and structural neuroimaging and genomic data to predict mental illness.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Neuropsychiatric disorders such as schizophrenia are very heterogeneous in nature and typically diagnosed using self-reported symptoms. This makes it difficult to pose a confident prediction on the cases and does not provide insight into the underlyi...

Schizophrenia Detection in Adolescents from EEG Signals using Symmetrically weighted Local Binary Patterns.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Schizophrenia is one of the most complex of all mental diseases. In this paper, we propose a symmetrically weighted local binary patterns (SLBP)-based automated approach for detection of schizophrenia in adolescents from electroencephalogram (EEG) si...

Multimodal Machine Learning Workflows for Prediction of Psychosis in Patients With Clinical High-Risk Syndromes and Recent-Onset Depression.

JAMA psychiatry
IMPORTANCE: Diverse models have been developed to predict psychosis in patients with clinical high-risk (CHR) states. Whether prediction can be improved by efficiently combining clinical and biological models and by broadening the risk spectrum to yo...

Two distinct neuroanatomical subtypes of schizophrenia revealed using machine learning.

Brain : a journal of neurology
Neurobiological heterogeneity in schizophrenia is poorly understood and confounds current analyses. We investigated neuroanatomical subtypes in a multi-institutional multi-ethnic cohort, using novel semi-supervised machine learning methods designed t...

Identifying Schizo-Obsessive Comorbidity by Tract-Based Spatial Statistics and Probabilistic Tractography.

Schizophrenia bulletin
A phenomenon in schizophrenia patients that deserves attention is the high comorbidity rate with obsessive-compulsive disorder (OCD). Little is known about the neurobiological basis of schizo-obsessive comorbidity (SOC). We aimed to investigate wheth...

Functional, Anatomical, and Morphological Networks Highlight the Role of Basal Ganglia-Thalamus-Cortex Circuits in Schizophrenia.

Schizophrenia bulletin
Evidence from electrophysiological, functional, and structural research suggests that abnormal brain connectivity plays an important role in the pathophysiology of schizophrenia. However, most previous studies have focused on single modalities only, ...