An electroencephalogram (EEG) is a test used to evaluate electrical activity in the brain and be used to detect certain brain disorders such as epilepsy. Event-related potentials (ERP) are obtained and analyzed. The advantage of using EEG scans stems from the ease of analysis due to its simple data type. However, EEG is not widely used for the diagnosis of mental disorders. This may be due to its low spatial resolution or depth sensitivity. Currently, there are differing views on the use of EEG as an effective tool to diagnose SZ [120,121,122,123,124]. In particular, it is criticized as it heavily depends on assumptions, conditions and prior knowledge regarding the patient. These may be improved through the use of data analysis and ML techniques [125]. An overview of the various study on machine learning techniques on EEG scan data is compiled in Table 4.

Summary of work and predictions relating to the detection of SZ using data from electroencephalogram scans via various artificial intelligence techniques and machine learning algorithms.

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