AIMC Topic: Schizophrenia
Clear Filters Showing 21 to 30 of 285 articles
Deep learning imputes DNA methylation states in single cells and enhances the detection of epigenetic alterations in schizophrenia.
Cell genomics
Feb 21, 2025
DNA methylation (DNAm) is a key epigenetic mark with essential roles in gene regulation, mammalian development, and human diseases. Single-cell technologies enable profiling DNAm at cytosines in individual cells, but they often suffer from low covera...
Multi-feature fusion method combining brain functional connectivity and graph theory for schizophrenia classification and neuroimaging markers screening.
Journal of psychiatric research
Feb 21, 2025
BACKGROUND: The abnormalities in brain functional connectivity (FC) and graph topology (GT) in patients with schizophrenia (SZ) are unclear. Researchers proposed machine learning algorithms by combining FC or GT to identify SZ from healthy controls. ...
Predicting mental health disparities using machine learning for African Americans in Southeastern Virginia.
Scientific reports
Feb 18, 2025
This study examined mental health disparities among African Americans using AI and machine learning for outcome prediction. Analyzing data from African American adults (18-85) in Southeastern Virginia (2016-2020), we found Mood Affective Disorders we...
Efficient Neural Network Classification of Parkinson's Disease and Schizophrenia Using Resting-State EEG Data.
Brain topography
Feb 17, 2025
Timely identification of Parkinson's disease and schizophrenia is crucial for the effective management and enhancement of patients' quality of life. The utilization of electroencephalogram (EEG) monitoring applications has proven instrumental in diag...
Predicting antipsychotic responsiveness using a machine learning classifier trained on plasma levels of inflammatory markers in schizophrenia.
Translational psychiatry
Feb 14, 2025
We apply machine learning techniques to navigate the multifaceted landscape of schizophrenia. Our method entails the development of predictive models, emphasizing peripheral inflammatory biomarkers, which are classified into treatment response subgro...
Schizophrenia recognition based on three-dimensional adaptive graph convolutional neural network.
Scientific reports
Feb 3, 2025
Previous deep learning-based brain network research has made significant progress in understanding the pathophysiology of schizophrenia. However, it ignores the three-dimensional spatial characteristics of EEG signals and cannot dynamically learn the...
Estimating the Prevalence of Schizophrenia in the General Population of Japan Using an Artificial Neural Network-Based Schizophrenia Classifier: Web-Based Cross-Sectional Survey.
JMIR formative research
Jan 29, 2025
BACKGROUND: Estimating the prevalence of schizophrenia in the general population remains a challenge worldwide, as well as in Japan. Few studies have estimated schizophrenia prevalence in the Japanese population and have often relied on reports from ...
A comparative machine learning study of schizophrenia biomarkers derived from functional connectivity.
Scientific reports
Jan 22, 2025
Functional connectivity holds promise as a biomarker of schizophrenia. Yet, the high dimensionality of predictive models trained on functional connectomes, combined with small sample sizes in clinical research, increases the risk of overfitting. Rece...
Schizophrenia more employable than depression? Language-based artificial intelligence model ratings for employability of psychiatric diagnoses and somatic and healthy controls.
PloS one
Jan 8, 2025
Artificial Intelligence (AI) assists recruiting and job searching. Such systems can be biased against certain characteristics. This results in potential misrepresentations and consequent inequalities related to people with mental health disorders. He...
MO-GCN: A multi-omics graph convolutional network for discriminative analysis of schizophrenia.
Brain research bulletin
Jan 7, 2025
The methodology of machine learning with multi-omics data has been widely adopted in the discriminative analyses of schizophrenia, but most of these studies ignored the cooperative interactions and topological attributes of multi-omics networks. In t...
Don't Miss the Future of Medicine
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.
Subscribe NowPopular Topics
- Machine Learning 31088
- Neural Networks, Computer 29743
- Algorithms 26874
- Deep Learning 26387
- Artificial Intelligence 24329
- Robotics 13315
- Image Processing, Computer-Assisted 9536
- Retrospective Studies 9125
- Magnetic Resonance Imaging 6192
- Reproducibility of Results 5600
- Tomography, X-Ray Computed 4772
- Support Vector Machine 4692
- Computational Biology 4243
- Brain 4053
- Computer Simulation 3885
Recent Journals
- Scientific reports 6015
- Sensors (Basel, Switzerland) 4794
- PloS one 4029
- Neural networks : the official journal of the International Neural Network Society 2930
- Computational intelligence and neuroscience 1931
- Computers in biology and medicine 1864
- Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference 1686
- Studies in health technology and informatics 1278
- IEEE journal of biomedical and health informatics 1133
- Journal of chemical information and modeling 1003
- Nature communications 952
- Computer methods and programs in biomedicine 883
- Bioinformatics (Oxford, England) 862
- Briefings in bioinformatics 853
- IEEE transactions on neural networks and learning systems 828