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---
dataset_info:
features:
- name: image
dtype: image
- name: label
dtype:
class_label:
names:
'0': Mild_Demented
'1': Moderate_Demented
'2': Non_Demented
'3': Very_Mild_Demented
splits:
- name: train
num_bytes: 22560791.2
num_examples: 5120
- name: test
num_bytes: 5637447.08
num_examples: 1280
download_size: 28289848
dataset_size: 28198238.28
license: apache-2.0
task_categories:
- image-classification
language:
- en
tags:
- medical
pretty_name: Alzheimer_MRI Disease Classification Dataset
size_categories:
- 1K<n<10K
---
# Alzheimer_MRI Disease Classification Dataset
The Falah/Alzheimer_MRI Disease Classification dataset is a valuable resource for researchers and health medicine applications. This dataset focuses on the classification of Alzheimer's disease based on MRI scans. The dataset consists of brain MRI images labeled into four categories:
- '0': Mild_Demented
- '1': Moderate_Demented
- '2': Non_Demented
- '3': Very_Mild_Demented
## Dataset Information
- Train split:
- Name: train
- Number of bytes: 22,560,791.2
- Number of examples: 5,120
- Test split:
- Name: test
- Number of bytes: 5,637,447.08
- Number of examples: 1,280
- Download size: 28,289,848 bytes
- Dataset size: 28,198,238.28 bytes
## Citation
If you use this dataset in your research or health medicine applications, we kindly request that you cite the following publication:
```
@dataset{alzheimer_mri_dataset,
author = {Falah.G.Salieh},
title = {Alzheimer MRI Dataset},
year = {2023},
publisher = {Hugging Face},
version = {1.0},
url = {https://huggingface.co/datasets/Falah/Alzheimer_MRI}
}
```
## Usage Example
Here's an example of how to load the dataset using the Hugging Face library:
```python
from datasets import load_dataset
# Load the Falah/Alzheimer_MRI dataset
dataset = load_dataset('Falah/Alzheimer_MRI', split='train')
# Print the number of examples and the first few samples
print("Number of examples:", len(dataset))
print("Sample data:")
for example in dataset[:5]:
print(example)
``` |