update

README.md

@@ -20,7 +20,68 @@ dataset_info:
     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
 ---
-# Dataset Card for "Alzheimer_MRI"
+# Alzheimer_MRI Disease Classification Dataset
 
-[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+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:
+
+@misc{falah_dataset_alzheimer_MRI,
+  author = {Falah G.Salieh},
+  title = {Falah/Alzheimer_MRI Disease Classification Dataset},
+  year = {2023},
+  publisher = {Falah Research Institute},
+  howpublished = {\url{https://huggingface.co/datasets/Falah/Alzheimer_MRI}},
+  note = {Dataset available from Hugging Face Datasets},
+}
+
+
+## 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)
+```