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Applying Artificial Intelligence (AI) in the healthcare domain is getting benefitted day by day with the advancement of approaches, one of them being Bio-Signal analysis. In Bio-signals, efficient feature engineering and feature extraction (FE) is necessary for optimal results. Features can be extracted from different methods by Time, Frequency, and Time-frequency domains. Time-frequency domain features are the most advanced and perform well for most AI-based signal analysis problems. We introduced the application of Wavelet Scattering Transform (WST) to neuro-disorder classification and provided a comparative study with Continuous Wavelet Transform (CWT) and Discrete Wavelet Transform (DWT) for schizophrenia disease classification. We are one of the first to apply WST to EEG data for classifying neurological disorders. We have also extracted 12 statistical features from the data before sending them to …