Psychiatry

Schizophrenia

Latest AI and machine learning research in schizophrenia for healthcare professionals.

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Subtyping first-episode psychosis based on longitudinal symptom trajectories using machine learning.

Clinical course after first episode psychosis (FEP) is heterogeneous. Subgrouping and predicting lon...

Degradation studies on lurasidone hydrochloride using validated reverse phase HPLC and LC-MS/MS.

1. The research aims to develop and validate a stability-indicating reverse phase high-performance l...

Improved serotonin neuron-specific viral vectors applicable for optogenetic manipulation and recording.

Serotonin neurons are central to the pathophysiology and therapeutics of mental disorders, including...

Tailored pharmacotherapy monitoring in Parkinson's disease and Schizophrenia using a rapid and sensitive α-Synuclein assay.

BACKGROUND: While Parkinson's disease is a low dopamine neurodegenerative disorder, Schizophrenia is...

AI-driven early diagnosis of specific mental disorders: a comprehensive study.

One of the areas where artificial intelligence (AI) technologies are used is the detection and diagn...

Visualizing functional network connectivity differences using an explainable machine-learning method.

. Functional network connectivity (FNC) estimated from resting-state functional magnetic resonance i...

Predictors of psychotic experiences among adolescents with obsessive-compulsive symptoms: A data-driven machine learning approach.

AIM: Prediction of future psychosis in individuals with obsessive and compulsive (OC) symptoms is cr...

Biological age prediction in schizophrenia using brain MRI, gut microbiome and blood data.

The study of biological age prediction using various biological data has been widely explored. Howev...

Predictive modeling of response to repetitive transcranial magnetic stimulation in treatment-resistant depression.

Identifying predictors of treatment response to repetitive transcranial magnetic stimulation (rTMS) ...

Brain circuits that regulate social behavior.

Social interactions are essential for the survival of individuals and the reproduction of population...

Understanding contraceptive switching rationales from real world clinical notes using large language models.

Understanding reasons for treatment switching is of significant medical interest, but these factors ...

Classification of schizophrenia spectrum disorder using machine learning and functional connectivity: reconsidering the clinical application.

BACKGROUND: Early identification of Schizophrenia Spectrum Disorder (SSD) is crucial for effective i...

Machine learning-based differentiation of schizophrenia and bipolar disorder using multiscale fuzzy entropy and relative power from resting-state EEG.

Schizophrenia (SZ) and bipolar disorder (BD) pose diagnostic challenges due to overlapping clinical ...

Classification of schizophrenia based on RAnet-ET: resnet based attention network for eye-tracking.

There is a notable need of quantifiable and objective methods for the classification of schizophreni...

Establishing a Validation Framework of Treatment Discontinuation in Claims Data Using Natural Language Processing and Electronic Health Records.

Measuring medication discontinuation in claims data primarily relies on the gaps between prescriptio...

Enhancing multiview synergy: Robust learning by exploiting the wave loss function with consensus and complementarity principles.

Multiview learning (MvL) is an advancing domain in machine learning, leveraging multiple data perspe...

Patient-specific MRI super-resolution via implicit neural representations and knowledge transfer.

Magnetic resonance imaging (MRI) is a non-invasive imaging technique that provides high soft tissue ...

Association of the characteristics of brain magnetic resonance imaging with genes related to disease onset in schizophrenia patients.

BACKGROUND: Schizophrenia (SCH) is a complex neurodevelopmental disorder, whose pathogenesis is not ...

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