ArticlePloS one2015
Schizophrenia detection and classification by advanced analysis of EEG recordings using a single electrode approach.
Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed.
- SchizoLMNet: a modified lightweight MobileNetV2- architecture for automated schizophrenia detection using EEG-derived spectrograms.Physical and engineering sciences in medicine · 2025Article
- EEG-based schizophrenia diagnosis using deep learning with multi-scale and adaptive feature selection.PeerJ. Computer science · 2025Article
- Multiresolution feature fusion for smart diagnosis of schizophrenia in adolescents using EEG signals.Cognitive neurodynamics · 2024Article
- Power spectral density-based resting-state EEG classification of first-episode psychosis.Scientific reports · 2024Article
- A deep learning approach for diagnosis of schizophrenia disorder via data augmentation based on convolutional neural network and long short-term memory.Biomedical engineering letters · 2024Article
- Brain functional connectivity based on phase lag index of electroencephalography for automated diagnosis of schizophrenia using residual neural networks.Journal of applied clinical medical physics · 2023Article
- Multimodal Assessment of Schizophrenia and Depression Utilizing Video, Acoustic, Locomotor, Electroencephalographic, and Heart Rate Technology: Protocol for an Observational Study.JMIR research protocols · 2022Article
- Comparison of Machine Learning Algorithms in the Prediction of Hospitalized Patients with Schizophrenia.Sensors (Basel, Switzerland) · 2022Article
- A deep learning approach in automated detection of schizophrenia using scalogram images of EEG signals.Physical and engineering sciences in medicine · 2022Article
- Implication of Electrophysiological Biomarkers in Psychosis: Focusing on Diagnosis and Treatment Response.Journal of personalized medicine · 2022Review
- Signaleeg : A practical tool for EEG signal data mining.Neuroinformatics · 2021Article
- Automated detection of schizophrenia using optimal wavelet-basedCognitive neurodynamics · 2021Article
- Schizophrenia: A Survey of Artificial Intelligence Techniques Applied to Detection and Classification.International journal of environmental research and public health · 2021Review
- Article
- Transfer learning with deep convolutional neural network for automated detection of schizophrenia from EEG signals.Physical and engineering sciences in medicine · 2020Article
- Genome-Wide Scan for Five Brain Oscillatory Phenotypes Identifies a New QTL Associated with Theta EEG Band.Brain sciences · 2020Article
- Connectivity maps based analysis of EEG for the advanced diagnosis of schizophrenia attributes.PloS one · 2017Article
- Artificial intelligence-based classification of schizophrenia: A high density electroencephalographic and support vector machine study.Indian journal of psychiatryArticle
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Electroencephalographic (EEG) analysis has emerged as a powerful tool for brain state interpretation and diagnosis, but not for the diagnosis of mental disorders; this may be explained by its low spatial resolution or depth sensitivity. This paper concerns the diagnosis of schizophrenia using EEG, which currently suffers from several cardinal problems: it heavily depends on assumptions, conditions and prior knowledge regarding the patient. Additionally, the diagnostic experiments take hours, and the accuracy of the analysis is low or unreliable. This article presents the "TFFO" (Time-Frequency transformation followed by Feature-Optimization), a novel approach for schizophrenia detection showing great success in classification accuracy with no false positives. The methodology is designed for single electrode recording, and it attempts to make the data acquisition process feasible and quick for most patients.
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