CNN Model Configuration for Schizophrenia Detection Research

Aggregating the configuration details for a Convolutional Neural Network (CNN) model used in a study on schizophrenia detection. The model is part of a framework exploring brain lobe data and explainable artificial intelligence (XAI) methods. The dataset is 5.5 KB in size and is provided in XLS format.

Use Cases

• Replicate the CNN model architecture described in the associated schizophrenia detection study
• Analyze the model configuration in relation to features like Brain Lobes or Time Fourier Transform mentioned in the tags
• Use the configuration as a baseline for experiments with other brain region data, such as Occipital Lobe or Frontal Lobe

Strengths

• Dataset is small (5.5 KB), facilitating quick download and inspection
• Released under a permissive CC BY 4.0 license, allowing for reuse and modification
• Associated with research on enhancing schizophrenia detection using Convolutional Neural Networks

Limitations

• Very small scale (5.5 KB), indicating it contains only model parameters or a brief description, not a full training dataset
• No sample data or column definitions are provided, limiting understanding of the data structure
• The description is minimal, offering no details on model performance, training data, or specific hyperparameters

Provenance

Source

figshare

Collection Method

Presumably created as part of the author's research methodology for model specification.

Freshness

Last updated on 2026-03-20.