AIMC Topic: Schizophrenia
Clear Filters Showing 261 to 270 of 287 articles
Multi-modal deep learning of functional and structural neuroimaging and genomic data to predict mental illness.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Nov 1, 2021
Neuropsychiatric disorders such as schizophrenia are very heterogeneous in nature and typically diagnosed using self-reported symptoms. This makes it difficult to pose a confident prediction on the cases and does not provide insight into the underlyi...
Schizophrenia Detection in Adolescents from EEG Signals using Symmetrically weighted Local Binary Patterns.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Nov 1, 2021
Schizophrenia is one of the most complex of all mental diseases. In this paper, we propose a symmetrically weighted local binary patterns (SLBP)-based automated approach for detection of schizophrenia in adolescents from electroencephalogram (EEG) si...
Multimodal Machine Learning Workflows for Prediction of Psychosis in Patients With Clinical High-Risk Syndromes and Recent-Onset Depression.
JAMA psychiatry
Feb 1, 2021
IMPORTANCE: Diverse models have been developed to predict psychosis in patients with clinical high-risk (CHR) states. Whether prediction can be improved by efficiently combining clinical and biological models and by broadening the risk spectrum to yo...
Machine learning-guided intervention trials to predict treatment response at an individual patient level: an important second step following randomized clinical trials.
Molecular psychiatry
Apr 1, 2020
Two distinct neuroanatomical subtypes of schizophrenia revealed using machine learning.
Brain : a journal of neurology
Mar 1, 2020
Neurobiological heterogeneity in schizophrenia is poorly understood and confounds current analyses. We investigated neuroanatomical subtypes in a multi-institutional multi-ethnic cohort, using novel semi-supervised machine learning methods designed t...
Identifying Schizo-Obsessive Comorbidity by Tract-Based Spatial Statistics and Probabilistic Tractography.
Schizophrenia bulletin
Feb 26, 2020
A phenomenon in schizophrenia patients that deserves attention is the high comorbidity rate with obsessive-compulsive disorder (OCD). Little is known about the neurobiological basis of schizo-obsessive comorbidity (SOC). We aimed to investigate wheth...
Functional, Anatomical, and Morphological Networks Highlight the Role of Basal Ganglia-Thalamus-Cortex Circuits in Schizophrenia.
Schizophrenia bulletin
Feb 26, 2020
Evidence from electrophysiological, functional, and structural research suggests that abnormal brain connectivity plays an important role in the pathophysiology of schizophrenia. However, most previous studies have focused on single modalities only, ...
Systematic Review of Digital Phenotyping and Machine Learning in Psychosis Spectrum Illnesses.
Harvard review of psychiatry
Jan 1, 2020
BACKGROUND: Digital phenotyping is the use of data from smartphones and wearables collected in situ for capturing a digital expression of human behaviors. Digital phenotyping techniques can be used to analyze both passively (e.g., sensor) and activel...
Hierarchical Structured Sparse Learning for Schizophrenia Identification.
Neuroinformatics
Jan 1, 2020
Fractional amplitude of low-frequency fluctuation (fALFF) has been widely used for resting-state functional magnetic resonance imaging (rs-fMRI) based schizophrenia (SZ) diagnosis. However, previous studies usually measure the fALFF within low-freque...
Machine learning technique reveals intrinsic characteristics of schizophrenia: an alternative method.
Brain imaging and behavior
Oct 1, 2019
Machine learning technique has long been utilized to assist disease diagnosis, increasing clinical physicians' confidence in their decision and expediting the process of diagnosis. In this case, machine learning technique serves as a tool for disting...
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 31213
- Neural Networks, Computer 29799
- Algorithms 26936
- Deep Learning 26448
- Artificial Intelligence 24385
- Robotics 13324
- Image Processing, Computer-Assisted 9558
- Retrospective Studies 9147
- Magnetic Resonance Imaging 6205
- Reproducibility of Results 5604
- Tomography, X-Ray Computed 4783
- Support Vector Machine 4700
- Computational Biology 4257
- Brain 4056
- Computer Simulation 3887
Recent Journals
- Scientific reports 6162
- Sensors (Basel, Switzerland) 4794
- PloS one 4061
- Neural networks : the official journal of the International Neural Network Society 2930
- Computational intelligence and neuroscience 1931
- Computers in biology and medicine 1868
- 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 1141
- Journal of chemical information and modeling 1016
- Nature communications 968
- Computer methods and programs in biomedicine 883
- Bioinformatics (Oxford, England) 863
- Briefings in bioinformatics 853
- IEEE transactions on neural networks and learning systems 830