Update README.md

README.md

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----
-license: apache-2.0
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+---
+license: apache-2.0
+task_categories:
+- image-classification
+language:
+- en
+pretty_name: RSNAICHMIL
+---
+# RSNA-ICH - Multiple Instance Learning (MIL)
+
+*Important.* This dataset is part of the [**torchmil** library](https://franblueee.github.io/torchmil/).
+
+This repository provides an adapted version of the [RSNA Intra-Cranial Hemorrhage (RSNA-ICH) Detection dataset](https://www.kaggle.com/competitions/rsna-intracranial-hemorrhage-detection) tailored for **Multiple Instance Learning (MIL)**. It is designed for use with the [`RSNAMILDataset`](https://franblueee.github.io/torchmil/api/datasets/rsnamil_dataset/) class from the [**torchmil** library](https://franblueee.github.io/torchmil/). RSNA-ICH is a widely used benchmark in MIL research, making this adaptation particularly valuable for developing and evaluating MIL models.
+
+### About the Original RSNA-ICH Dataset
+
+The original [RSNA-ICH dataset](https://www.kaggle.com/competitions/rsna-intracranial-hemorrhage-detection) contains head CT scans. The task is to identify whether a CT scan contains acute intracranial hemorrhage and its subtypes. The dataset includes a label for each slice. 
+
+### Dataset Description
+
+We have preprocessed the CT scans by computing features for each slice using various feature extractors.
+
+- A **slice** is labeled as positive (`slice_label=1`) if it contains evidence of hemorrhage.
+- A **CT scan** is labeled as positive (`label=1`) if it contains at least one positive slice.
+
+This means a CT scan is considered positive if there is any evidence of hemorrhage.
+
+### Directory Structure
+
+After extracting the contents of the `.tar.gz` archives, the following directory structure is expected:
+
+```
+root
+├── features
+│   ├── features_{features}
+│   │   ├── ctscan_name1.npy
+│   │   ├── ctscan_name2.npy
+│   │   └── ...
+├── labels
+│   ├── ctscan_name1.npy
+│   ├── ctscan_name2.npy
+│   └── ...
+├── slice_labels
+│   ├── ctscan_name1.npy
+│   ├── ctscan_name2.npy
+│   └── ...
+└── splits.csv
+```
+
+Each `.npy` file corresponds to a single CT scan. The `splits.csv` file defines train/test splits for standardized experimentation.
+
+