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Duplicate
The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code:   StreamingRowsError
Exception:    ImportError
Message:      To support decoding NIfTI files, please install 'nibabel'.
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 99, in get_rows_or_raise
                  return get_rows(
                         ^^^^^^^^^
                File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
                  return func(*args, **kwargs)
                         ^^^^^^^^^^^^^^^^^^^^^
                File "/src/services/worker/src/worker/utils.py", line 77, in get_rows
                  rows_plus_one = list(itertools.islice(ds, rows_max_number + 1))
                                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2690, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2240, in __iter__
                  example = _apply_feature_types_on_example(
                            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2159, in _apply_feature_types_on_example
                  decoded_example = features.decode_example(encoded_example, token_per_repo_id=token_per_repo_id)
                                    ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 2204, in decode_example
                  column_name: decode_nested_example(feature, value, token_per_repo_id=token_per_repo_id)
                               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 1508, in decode_nested_example
                  return schema.decode_example(obj, token_per_repo_id=token_per_repo_id) if obj is not None else None
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/features/nifti.py", line 172, in decode_example
                  raise ImportError("To support decoding NIfTI files, please install 'nibabel'.")
              ImportError: To support decoding NIfTI files, please install 'nibabel'.

Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.

automedbench-seg-task-data

Data mirror for the segmentation branch of AutoMedBench. Pulled automatically by the sandbox repo MitakaKuma/automedbench-seg-task.

Hosted tasks: kidney · liver · pancreas · aeropath · tsg-multiorgan. Bring-your-own tasks (license forbids redistribution): pancreas-oar · feta.

📘 Full dataset sources, licenses, and access terms: github.com/AutoMedBench/AutoMedBench/blob/main/docs/dataset-collection.md

Layout

<task_data_dir>/
  public/<patient_id>/     inputs the agent sees
  private/<patient_id>/    ground-truth masks

Use via sandbox (recommended)

git clone https://huggingface.co/MitakaKuma/automedbench-seg-task
cd automedbench-seg-task
./bootstrap_data.sh

Disclaimer

This mirror is provided for reproducibility of the AutoMedBench benchmark. Each dataset here remains governed by its original license — always verify on the source page and credit the original authors.

Citation

@misc{liu2026automedbench,
  author = {Liu, Junqi and Song, Salena and Wang, Yuhan and Mao, Jiawei and Chen, Guiming and Huang, Xiaoke and Qi, Tianhao and Tang, Yucheng and Xu, Daguang and Zhou, Yuyin},
  title  = {AutoMedBench: Towards Medical AutoResearch},
  year   = {2026},
  url    = {https://github.com/AutoMedBench/AutoMedBench},
}

Also cite each task's source dataset per its own citation policy.

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