SIDER_gastro

Part of TabBioMed (TabBioMed: A Large-Scale Benchmark for Biomedical Tabular Learning), a benchmark of 94 curated biomedical tabular datasets. Code, preprocessing and documentation: https://github.com/AI-sandbox/TabBioMed.

Database of marketed drugs and adverse drug reactions (ADR) grouped into 27 system organ classes. Task: predict 'Gastrointestinal disorders'. Features: Morgan fingerprints (radius=2).

Domain	Task	Samples	Features	Classes
Drug Discovery	binary	1,427	2,018	2

Splits. Fixed train/val/test split (998/214/215 rows).

Files

• data/**.parquet: one row per sample. row_idx is the row index in the original TabBioMed array; f_<i>[_<name>] are the features (in order); target (or target_<j> for multi-target tasks) is the label. Categorical feature indices (0-based, among the features): []. Missing values are stored as nulls.
• metadata.json: TabBioMed task metadata (task type, categorical indices, source, description).

from datasets import load_dataset
ds = load_dataset("TabBioMed/SIDER_gastro")

A Croissant (1.1) description with Responsible-AI fields is distributed with the TabBioMed release.

Source and license

Dataset license: CC-BY-SA-4.0.

• SIDER 4.1, MedDRA side-effect mappings. Kuhn et al. (2016), DOI 10.1093/nar/gkv1075. MoleculeNet: Wu et al., DOI 10.1039/C7SC02664A. Source license: CC-BY-SA-4.0. Retain attribution and the license link, identify modifications, and do not imply endorsement. Shared adaptations of the side-effect mappings retain CC BY-SA 4.0. The CC0 labels on README and drug-name files do not apply to the side-effect data.

See NOTICE.md for attribution and modifications and LICENSES/ for license texts.

Citation

@inproceedings{tabbiomed2026,
  title     = {TabBioMed: A Large-Scale Benchmark for Biomedical Tabular Learning},
  author    = {Mateo Bernad{\'o}, Pau and Polapragada, Saivenkata Nagavyjayanthi and Bonet, David and Arbiol Rakuljic, Pol and Mogas Pladevall, Laia and Comajoan Cara, Mar{\c{c}}al and Gonzalez Ferrer, Jesus and Abante, Jordi and Mas Montserrat, Daniel and Haussler, David and Ioannidis, Alexander G.},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS), Evaluations and Datasets Track},
  year      = {2026}
}