Automated detection of schizophrenia using deep learning: a review for the last decade
Article
Sharma, Manish, Patel, Ruchit Kumar, Garg, Akshat, Tan, Ru San and Acharya, U Rajendra. 2023. "Automated detection of schizophrenia using deep learning: a review for the last decade." Physiological Measurement. 44 (3). https://doi.org/10.1088/1361-6579/acb24d
Article Title | Automated detection of schizophrenia using deep learning: a review for the last decade |
---|---|
Article Category | Article |
Authors | Sharma, Manish, Patel, Ruchit Kumar, Garg, Akshat, Tan, Ru San and Acharya, U Rajendra |
Journal Title | Physiological Measurement |
Journal Citation | 44 (3) |
Article Number | 03TR01 |
Number of Pages | 24 |
Year | 2023 |
Place of Publication | Netherlands |
Digital Object Identifier (DOI) | https://doi.org/10.1088/1361-6579/acb24d |
Web Address (URL) | https://iopscience.iop.org/article/10.1088/1361-6579/acb24d |
Abstract | Schizophrenia (SZ) is a devastating mental disorder that disrupts higher brain functions like thought, perception, etc., with a profound impact on the individual's life. Deep learning (DL) can detect SZ automatically by learning signal data characteristics hierarchically without the need for feature engineering associated with traditional machine learning. We performed a systematic review of DL models for SZ detection. Various deep models like long short-term memory, convolution neural networks, AlexNet, etc., and composite methods have been published based on electroencephalographic signals, and structural and/or functional magnetic resonance imaging acquired from SZ patients and healthy patients control subjects in diverse public and private datasets. The studies, the study datasets, and model methodologies are reported in detail. In addition, the challenges of DL models for SZ diagnosis and future works are discussed. |
Keywords | convolutional neural networks; schizophrenia; electroencephalography (EEG); long short-term memory; functional magnetic resonance imaging; deep learning |
ANZSRC Field of Research 2020 | 400306. Computational physiology |
Public Notes | Files associated with this item cannot be displayed due to copyright restrictions. |
Byline Affiliations | Institute of Infrastructure, Technology, Research and Management (IITRAM), India |
National Heart Centre, Singapore | |
Ngee Ann Polytechnic, Singapore | |
Asia University, Taiwan | |
Centre for Health Research | |
National University of Singapore |
Permalink -
https://research.usq.edu.au/item/z1w16/automated-detection-of-schizophrenia-using-deep-learning-a-review-for-the-last-decade
62
total views0
total downloads2
views this month0
downloads this month