Latest AI and machine learning research in schizophrenia for healthcare professionals.
BACKGROUND: This study analyzed plasma cytokine patterns in individuals with schizophrenia (SCZ), major depressive disorder (MDD), and healthy controls, explored the link between cytokine levels and cognitive function, and created machine learning models to evaluate the diagnostic potential of cytokine and cognitive assessments.
Approaches studying the dynamics of resting-state functional magnetic resonance imaging (rs-fMRI) activity often focus on time-resolved functional connectivity (tr-FC). While many tr-FC approaches have been proposed, most are linear approaches, e.g. computing the linear correlation at a timestep or within a window. In this work, we propose to use a generative non-linear deep learning model, a dise...
BACKGROUND: The thalamus plays a crucial role in sensory processing, emotional regulation, and cognitive functions, and its dysregulation may be impli...
Repetitive transcranial magnetic stimulation (rTMS) is a potential treatment for schizophrenia (SCZ), yet its efficacy and underlying mechanisms remai...
In recent years, large language models (LLMs) represented by GPT-4 have developed rapidly and performed well in various natural language processing ta...
Tardive dyskinesia (TD) is a late-onset adverse effect of dopamine receptor-blocking medications, characterized by involuntary movements primarily af...
Machine learning applications in schizophrenia neuroimaging research have undergone significant evolution since 2012. However, a comprehensive sciento...
Alterations in social functioning are commonly observed in youth at clinical high risk (CHR) for psychosis. Previous research has focused on perceptio...
Person re-identification (re-ID) models often fail to generalize well when deployed to other camera networks with domain shift. A classical domain gen...
Motor activity alterations are key symptoms of psychiatric disorders like schizophrenia. Actigraphy, a non-invasive monitoring method, shows promise i...
While white matter myelin primarily functions to accelerate conduction velocity and has been extensively studied in schizophrenia-spectrum disorders (...
BACKGROUND AND HYPOTHESIS: The multifactorial pathogenesis of schizophrenia (SZ) hinders the diagnosis and treatment of this disorder. Niacin skin flu...
BACKGROUND: Artificial intelligence (AI) offers an innovative means of changing primary care, yet the impressions of primary care professionals (PCPs)...
Small cyclic peptides have gained significant traction as a therapeutic modality; however, the development of deep learning methods for accurately des...
BACKGROUND: Over the last decade, there has been considerable development in precision psychiatry, especially in the development of novel prediction t...
Artificial intelligence (AI) is increasingly being applied to clinical cancer research, driving precision oncology objectives by gathering clinical da...
BACKGROUND: We previously proposed a neurocognitive model of psychosis in which reduced morphometric hippocampal-cortical connectivity precedes impair...
Topological indices are invariant quantitative metrics associated with a molecular graph, which characterize the bonding topology of a molecule. The m...
Clinical course after first episode psychosis (FEP) is heterogeneous. Subgrouping and predicting longitudinal symptom trajectories after FEP may help ...
1. The research aims to develop and validate a stability-indicating reverse phase high-performance liquid chromatography (RP-HPLC) method for Lurasido...