Latest AI and machine learning research in schizophrenia for healthcare professionals.
Drug discovery relies on the precise prognosis of drug-target interactions (DTI). Due to their ability to learn from raw data, deep learning (DL) methods have displayed outstanding performance over traditional approaches. However, challenges such as imbalanced data, noise, poor generalization, high cost, and time-consuming processes hinder progress in this field. To overcome the above challenges, ...
Machine learning approaches using structural magnetic resonance imaging (sMRI) can be informative for disease classification, although their ability to predict psychosis is largely unknown. We created a model with individuals at CHR who developed psychosis later (CHR-PS+) from healthy controls (HCs) that can differentiate each other. We also evaluated whether we could distinguish CHR-PS+ individua...
Functional near-infrared spectroscopy (fNIRS) and its interaction with machine learning (ML) is a popular research topic for the diagnostic classifica...
Automated speech analysis techniques, when combined with artificial intelligence and machine learning, show potential in capturing and predicting a wi...
As interpersonal synchrony plays a key role in building rapport, the perception of another agent's synchronizing behavior could be an important featur...
INTRODUCTION: Visual hallucination is a prevalent psychiatric disorder characterized by the occurrence of false visual perceptions due to misinterpret...
It is widely hoped that statistical models can improve decision-making related to medical treatments. Because of the cost and scarcity of medical outc...
UNLABELLED: Disorders of systemic immunity and immune processes in the brain have now been shown to play an essential role in the development and prog...
BACKGROUND: Mood disorders and schizophrenia affect millions worldwide. Currently, diagnosis is primarily determined by reported symptomatology. As sy...
Blunted affect is associated with severe mental illness, particularly schizophrenia. Mechanisms of blunted affect are poorly understood, potentially d...
As one of the largest contributors of morbidity and mortality, psychiatric disorders are anticipated to triple in prevalence over the coming decade or...
BACKGROUND: Schizophrenia is a severe psychiatric disorder associated with a significant negative impact. Early diagnosis and treatment of schizophren...
(SCZ) is a severe mental disorder associated with persistent or recurrent psychosis, hallucinations, delusions, and thought disorders that affect appr...
Ecological momentary assessment (EMA), a structured diary assessment technique, has shown feasibility to capture psychotic(-like) symptoms across diff...
OBJECTIVES: This study aimed at identifying reliable differentially expressed miRNAs (DEMs) for schizophrenia in blood meta-analyses combined with de...
Forensic psychiatric populations commonly contain a subset of persons with schizophrenia spectrum disorders (SSD) who have committed sex offenses. A c...
Electroencephalography is a method of detecting and analyzing electrical activity in the brain. This electrical activity can be recorded and processed...
Schizophrenia is a chronic neuropsychiatric disorder that causes distinct structural alterations within the brain. We hypothesize that deep learning a...
The genetic etiology of brain disorders is highly heterogeneous, characterized by abnormalities in the development of the central nervous system that ...