AIMC Topic: Schizophrenia
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Hugan Tiaoshen Formula Improves the Comorbid Mechanism of Schizophrenia and Sleep Disorder via Multitarget Interaction Network.
FASEB journal : official publication of the Federation of American Societies for Experimental Biology
Jun 30, 2025
This study aims to integrate cross-disease omics data and perform multidimensional analysis to uncover the molecular basis of schizophrenia (SCZ) and sleep disorder (SD) comorbidity and to systematically analyze the potential mechanism of the Hugan T...
A highly scalable deep learning language model for common risks prediction among psychiatric inpatients.
BMC medicine
May 28, 2025
BACKGROUND: There is a lack of studies exploring the performance of Transformers-based language models in common risks assessment among psychiatric inpatients. We aim to develop a scalable risk assessment model using multidimensional textualized data...
Hearing vocals to recognize schizophrenia: speech discriminant analysis with fusion of emotions and features based on deep learning.
BMC psychiatry
May 8, 2025
BACKGROUND AND OBJECTIVE: Accurate detection of schizophrenia poses a grand challenge as a complex and heterogeneous mental disorder. Current diagnostic criteria rely primarily on clinical symptoms, which may not fully capture individual differences ...
EEG-based Signatures of Schizophrenia, Depression, and Aberrant Aging: A Supervised Machine Learning Investigation.
Schizophrenia bulletin
May 8, 2025
BACKGROUND: Electroencephalography (EEG) is a noninvasive, cost-effective, and robust tool, which directly measures in vivo neuronal mass activity with high temporal resolution. Combined with state-of-the-art machine learning (ML) techniques, EEG rec...
Predicting Diagnostic Progression to Schizophrenia or Bipolar Disorder via Machine Learning.
JAMA psychiatry
May 1, 2025
IMPORTANCE: The diagnosis of schizophrenia and bipolar disorder is often delayed several years despite illness typically emerging in late adolescence or early adulthood, which impedes initiation of targeted treatment.
Neuroimage Analysis Methods and Artificial Intelligence Techniques for Reliable Biomarkers and Accurate Diagnosis of Schizophrenia: Achievements Made by Chinese Scholars Around the Past Decade.
Schizophrenia bulletin
Mar 14, 2025
BACKGROUND AND HYPOTHESIS: Schizophrenia (SZ) is characterized by significant cognitive and behavioral disruptions. Neuroimaging techniques, particularly magnetic resonance imaging (MRI), have been widely utilized to investigate biomarkers of SZ, dis...
Eye Movement Characteristics for Predicting a Transition to Psychosis: Longitudinal Changes and Implications.
Schizophrenia bulletin
Mar 14, 2025
BACKGROUND AND HYPOTHESIS: Substantive inquiry into the predictive power of eye movement (EM) features for clinical high-risk (CHR) conversion and their longitudinal trajectories is currently sparse. This study aimed to investigate the efficiency of ...
Semantic abnormalities in schizophrenia and bipolar disorder: A natural language processing approach.
Science progress
Jan 1, 2025
INTRODUCTION: The diagnostic boundaries between schizophrenia and bipolar disorder are controversial due to the ambiguity of psychiatric nosology. From this perspective, it is noteworthy that formal thought disorder has historically been considered p...
Diagnosis of Schizophrenia and Its Subtypes Using MRI and Machine Learning.
Brain and behavior
Jan 1, 2025
PURPOSE: The neurobiological heterogeneity present in schizophrenia remains poorly understood. This likely contributes to the limited success of existing treatments and the observed variability in treatment responses. Our objective was to employ magn...
Deconstructing Cognitive Impairment in Psychosis With a Machine Learning Approach.
JAMA psychiatry
Jan 1, 2025
IMPORTANCE: Cognitive functioning is associated with various factors, such as age, sex, education, and childhood adversity, and is impaired in people with psychosis. In addition to specific effects of the disorder, cognitive impairments may reflect a...
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