Datasets:
|
Download README.md from Edwin0080/Auto-MD-bench: direct link, hf CLI and curl.
- Browser
- Download file 5.39 kB
-
https://huggingface.co/datasets/Edwin0080/Auto-MD-bench/resolve/main/README.md
- Command line
-
hf download hf://datasets/Edwin0080/Auto-MD-bench/README.md
-
curl -L -o README.md https://huggingface.co/datasets/Edwin0080/Auto-MD-bench/resolve/main/README.md
5.39 kB
| pretty_name: Auto-MD-bench | |
| license: other | |
| license_name: mixed | |
| license_link: LICENSE | |
| language: | |
| - en | |
| tags: | |
| - medical | |
| - clinical-prediction | |
| - survival-analysis | |
| - benchmark | |
| - agents | |
| task_categories: | |
| - tabular-classification | |
| size_categories: | |
| - 1M<n<10M | |
| viewer: false | |
| # Auto-MD-bench: task packages | |
| Auto-MD-bench evaluates autoresearch agents that build prediction models for medical tasks. An agent | |
| receives a task description and labeled training data, develops a model on its own within a fixed | |
| time budget, and submits predictions for a hidden test set. Submissions are scored on the task's | |
| primary metric, on risk calibration and on performance under population shift. | |
| This repository holds the ready-built packages of the 10 benchmark tasks that use public data, plus | |
| the two objective variants of `uci_diabetes` used in the calibration experiment. The other 5 tasks use | |
| MIMIC-IV, eICU-CRD and SEER, which cannot be redistributed; build them from the scripts in the code | |
| repository after obtaining access. | |
| Paper: https://arxiv.org/abs/2610.25069 | |
| Code, agents, grader and paper results: https://github.com/Edwin0080/Auto-MD-bench | |
| ## Tasks in this repository | |
| | Task | Data | Outcome | Validation | Primary metric | Train / test | | |
| |---|---|---|---|---|---| | |
| | `support` | SUPPORT | Death | Internal | C<sup>td</sup> | 7,098 / 1,775 | | |
| | `metabric` | METABRIC | Death | Internal | C<sup>td</sup> | 1,523 / 381 | | |
| | `rotterdam` | Rotterdam | Recurrence or death | Internal | C<sup>td</sup> | 2,385 / 597 | | |
| | `rotterdam_gbsg` | Rotterdam → GBSG | Recurrence or death | External (cohort) | C<sup>td</sup> | 2,982 / 686 | | |
| | `nhanes` | NHANES | Death | Internal | C<sup>td</sup> | 11,639 / 2,910 | | |
| | `uci_diabetes` | UCI Diabetes, 130 US hospitals | 30-day readmission | Internal | AUROC | 81,347 / 20,419 encounters | | |
| | `physionet2012` | PhysioNet/CinC 2012, ICU | In-hospital death | Internal | min(Se, PPV) | 4,000 / 8,000 stays | | |
| | `sepsis` | PhysioNet/CinC 2019, ICU | Sepsis onset | Internal | Utility | 32,268 / 8,068 | | |
| | `sepsis_new_hospital` | PhysioNet/CinC 2019, ICU | Sepsis onset | External (hospital) | Utility | 20,336 / 4,000 | | |
| | `sepsis_500_labels` | PhysioNet/CinC 2019, ICU | Sepsis onset | External (hospital) | Utility | 20,336 + 500 / 4,000 | | |
| `uci_diabetes_brier` and `uci_diabetes_ece` have the same data as `uci_diabetes`; only the stated | |
| objective in `description.md` differs (Brier score; AUROC and ECE). | |
| Not here (build locally): `seer`, `seer_later_period` (SEER Research Data Agreement), `mimiciv`, `eicu`, | |
| `eicu_new_hospitals` (PhysioNet credentialed access). | |
| ## Layout | |
| ``` | |
| <task>/ | |
| public/ what the agent sees: description.md, training data, test features, | |
| sample_submission.csv, validate.py (format checker) | |
| private/ hidden test labels, used only by the grader | |
| ``` | |
| Give an agent only `public/`. The data are the same as in the paper's experiments. | |
| ## Usage | |
| ```bash | |
| pip install -U huggingface_hub | |
| git clone https://github.com/Edwin0080/Auto-MD-bench && cd Auto-MD-bench | |
| pip install -e . | |
| hf download Edwin0080/Auto-MD-bench --repo-type dataset --local-dir packages | |
| python -m automdbench.grade support packages/support/public/sample_submission.csv | |
| ``` | |
| See the code repository for running agents and for the scoring protocol. | |
| ## Data sources and licenses | |
| Each task keeps the license of its source data. Cite the sources below when you use the tasks. | |
| | Tasks | Source | License or terms | | |
| |---|---|---| | |
| | `support` | SUPPORT (Knaus et al., 1995), as processed by DeepSurv (Katzman et al., 2018) from the Vanderbilt Biostatistics data repository | "Permission is granted to anyone wishing to use the data sets"; data obtained from https://hbiostat.org/data courtesy of the Vanderbilt University Department of Biostatistics | | |
| | `metabric` | METABRIC (Curtis et al., 2012; Pereira et al., 2016; Rueda et al., 2019), as processed by DeepSurv; the same values are in cBioPortal `brca_metabric` | ODC Open Database License (ODbL) 1.0, as distributed by cBioPortal | | |
| | `rotterdam`, `rotterdam_gbsg` | Rotterdam tumour bank and GBSG trial (Royston and Altman, 2013), as distributed in the R package `survival` | LGPL (≥ 2), the license of the `survival` package | | |
| | `nhanes` | NHANES 2011–2016 and NCHS public-use linked mortality files | U.S. public-use data; NCHS data use restrictions apply (no attempt to identify individuals) | | |
| | `uci_diabetes*` | Diabetes 130-US Hospitals for Years 1999–2008, UCI Machine Learning Repository (Strack et al., 2014) | CC BY 4.0 | | |
| | `physionet2012` | PhysioNet/CinC Challenge 2012 (Silva et al., 2012; Goldberger et al., 2000) | Open Data Commons Attribution License 1.0 | | |
| | `sepsis*` | PhysioNet/CinC Challenge 2019 (Reyna et al., 2020; Goldberger et al., 2000) | CC BY 4.0 | | |
| The `sepsis*` packages include `utility_score.py`, the official PhysioNet/CinC Challenge 2019 scoring | |
| functions (BSD 2-Clause). The `validate.py` format checkers are part of the benchmark code (MIT). | |
| ## Citation | |
| ```bibtex | |
| @misc{zhou2026automdbenchevaluatingautoresearchagents, | |
| title={Auto-MD-bench: Evaluating Autoresearch Agents for Real-World Medical Tasks}, | |
| author={Shenqi Zhou and Qiran Zou and Wenhao Zhao and Zhenyu Liao and Dianbo Liu}, | |
| year={2026}, | |
| eprint={2610.25069}, | |
| archivePrefix={arXiv}, | |
| primaryClass={cs.LG}, | |
| url={https://arxiv.org/abs/2610.25069}, | |
| } | |
| ``` | |