TabBioMed camera-ready release

README.md

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+---
+license: odc-by
+pretty_name: IACCD
+task_categories:
+- tabular-classification
+tags:
+- tabular
+- biomedical
+- benchmark
+- TabBioMed
+- clinical-&-healthcare
+- binary
+size_categories:
+- 1K<n<10K
+configs:
+- config_name: default
+  data_files:
+  - split: train
+    path: data/train.parquet
+  - split: validation
+    path: data/val.parquet
+  - split: test
+    path: data/test.parquet
+---
+
+# IACCD
+
+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.
+
+Indwelling Arterial Catheter Clinical Dataset (IACCD) for 28-day mortality prediction. TabBioMed uses the separately released PhysioNet mimic2-iaccd dataset, available without credentialed access under the Open Data Commons Attribution License v1.0; it does not directly access the credentialed MIMIC-II database. The whole-stay blood-gas test count (abg_count) is excluded from predictors.
+
+| Domain | Task | Samples | Features | Classes |
+|---|---|---|---|---|
+| Clinical & Healthcare | binary | 1,776 | 34 | 2 |
+
+**Splits.** Fixed train/val/test split (1243/266/267 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): `[0, 2, 9, 10, 11, 12, 13, 14, 15, 16, 17, 7, 8]`. Missing values are stored as nulls.
+- `metadata.json`: TabBioMed task metadata (task type, categorical indices, source, description).
+- `feature_names.json`: original feature names, in column order.
+
+```python
+from datasets import load_dataset
+ds = load_dataset("TabBioMed/IACCD")
+```
+
+A Croissant (1.1) description with Responsible-AI fields is distributed with the
+TabBioMed release.
+
+## Source and license
+
+Source: PhysioNet mimic2-iaccd v1.0
+
+This derived dataset is distributed under ODC-By 1.0 (https://opendatacommons.org/licenses/by/1-0/). Please also
+cite and respect the terms of the original source.
+
+## Citation
+
+```bibtex
+@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}
+}
+```

data/test.parquet

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+version https://git-lfs.github.com/spec/v1
+oid sha256:0f9d1c92d1d66176bd98b913551f8182520d8a5a9da2bef5e3d650058e1a2043
+size 39892

data/train.parquet

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+version https://git-lfs.github.com/spec/v1
+oid sha256:57583ddbb4dd4eb55a32134d57fcf88dfcf11e029f269dcd5963322103b42a0f
+size 89770

data/val.parquet

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+version https://git-lfs.github.com/spec/v1
+oid sha256:adc699f4bfb0105326cd5b73eab0a71a4cccef017be7d4abc955650c99e1c241
+size 39845

feature_names.json

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+[
+  "aline_flg",
+  "age",
+  "gender_num",
+  "weight_first",
+  "bmi",
+  "sapsi_first",
+  "sofa_first",
+  "service_unit",
+  "day_icu_intime",
+  "chf_flg",
+  "afib_flg",
+  "renal_flg",
+  "liver_flg",
+  "copd_flg",
+  "cad_flg",
+  "stroke_flg",
+  "mal_flg",
+  "resp_flg",
+  "map_1st",
+  "hr_1st",
+  "temp_1st",
+  "spo2_1st",
+  "wbc_first",
+  "hgb_first",
+  "platelet_first",
+  "sodium_first",
+  "potassium_first",
+  "tco2_first",
+  "chloride_first",
+  "bun_first",
+  "creatinine_first",
+  "po2_first",
+  "pco2_first",
+  "iv_day_1"
+]

metadata.json

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+{
+  "READY": true,
+  "name": "IACCD",
+  "task": "binary",
+  "num_classes": 2,
+  "cat_idx": [
+    0,
+    2,
+    9,
+    10,
+    11,
+    12,
+    13,
+    14,
+    15,
+    16,
+    17,
+    7,
+    8
+  ],
+  "num_samples": 1776,
+  "num_features": 34,
+  "imbalance_ratio": 5.2756,
+  "description": "Indwelling Arterial Catheter Clinical Dataset (IACCD) for 28-day mortality prediction. TabBioMed uses the separately released PhysioNet mimic2-iaccd dataset, available without credentialed access under the Open Data Commons Attribution License v1.0; it does not directly access the credentialed MIMIC-II database. The whole-stay blood-gas test count (abg_count) is excluded from predictors.",
+  "source": "PhysioNet mimic2-iaccd v1.0",
+  "label": "clinical & healthcare",
+  "source_url": "https://physionet.org/content/mimic2-iaccd/1.0/",
+  "license": "ODC-By-1.0",
+  "license_url": "https://opendatacommons.org/licenses/by/1-0/",
+  "access_policy": "Open access; no credentials required",
+  "curation_protocol": "iaccd_no_abg_v1"
+}