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Schizo-xai: Schizophrenia Detection using Wavelet Transform and ResNet-18 🧠 📊

Overview

This project aims to detect schizophrenia using wavelet transform and a ResNet-18 based classification model. The utilization of wavelet transform allows for a detailed analysis of Electroencephalogram (EEG) data, providing valuable insights into the components of brain signals. You can access my bachelor's thesis here

Features

  • Schizophrenia detection through EEG data.
  • Wavelet transform for feature extraction.
  • ResNet-18 for classification.
  • GradCAM for explainability on wavelet scalograms.

Installation

  1. Clone the repository: 
    git clone https://github.com/Rish-01/Schizo-xai.git
cd Schizo-xai
  2. Install Dependencies: 
    pip install -r requirements.txt

Directory Structure

.
├── EEG_data
├── image_dir
│   ├── healthy
│   └── schizophrenic
├── model_checkpoints
├── requirements.txt
└── Schizo.ipynb