Latest AI and machine learning research in schizophrenia for healthcare professionals.
Multimodal neuroimaging is an emerging field that leverages multiple sources of information to diagn...
Evaluating the importance of different layers in large language models (LLMs) is crucial for optim...
Automatic feature recognition (AFR) is essential for transforming design knowledge into actionable...
Within-disorder heterogeneity complicates mapping the neurobiological features of psychopathology to...
Hallucination poses a challenge to the deployment of large vision-language models (LVLMs) in appli...
Hallucinations in multimodal large language models (MLLMs) hinder their practical applications. To...
Introduction Schizophrenia is a severe mental disorder, and early diagnosis is key to improving ou...
SUMMARY: The vast generation of genetic data poses a significant challenge in efficiently uncovering...
Extensive experiments suggest that motor coordination among human participants may contribute to s...
Schizophrenia genome-wide association studies (GWAS) have reported many genomic risk loci, but it is...
BACKGROUND: Schizophrenia is a complex and disabling mental disorder that represents one of the most...
Deep Learning (DL) in neuroimaging has become increasingly relevant for detecting neurological con...
Incomplete Hippocampal Inversion (IHI), sometimes called hippocampal malrotation, is an atypical a...
Schizophrenia (SZ) is a severe brain disorder marked by diverse cognitive impairments, abnormaliti...
BACKGROUND AND HYPOTHESIS: The brain-predicted age difference (brain-PAD) may serve as a biomarker f...
Investigating the genetic architecture of complex diseases is challenging due to the multifactoria...
Rapid advances in artificial intelligence (AI) have reshaped healthcare, including psychiatric nursi...
Hallucination has been a major problem for large language models and remains a critical challenge ...
One of the key challenges in the use of resting brain functional magnetic resonance imaging (fMRI) n...
Time courses (TC) and functional network connectivity (FNC) features, derived from functional magnet...
Neuroimaging data have become widely studied in the context of identifying brain-based markers of me...