datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
EHRSQL_PostgreSQL_data
EHRSQL PostgreSQL Artifacts
This dataset repository hosts database artifacts generated for the companion
GitHub repository:
https://github.com/Jensen-JinhuiLiu/EHRSQL_PostgreSQL
Files
eicu.sqlite: original benchmark SQLite database artifact used for eICU.
mimic_iii.sqlite: original benchmark SQLite database artifact used for MIMIC-III.
postgres_import/eicu/csv/: CSV exports for loading the eICU PostgreSQL database.
postgres_import/mimic_iii/csv/: CSV exports for… See the full description on the dataset page: https://huggingface.co/datasets/JimHue/EHRSQL_PostgreSQL_data.medical-ehr-training-data
Medical EHR Training Dataset
Training dataset for Medical EHR GEPA-optimized module.
Dataset Description
This dataset contains 382 medical EHR query examples for training DSPy GEPA optimization.
Dataset Structure
{
"query": "Show me diabetic patients",
"expected_strategy": "ENRICHMENT",
"expected_snomed_codes": ["73211009", "44054006"],
"expected_neo4j_count": 15,
"query_complexity": "simple",
"medical_category": "endocrine"
}
Splits… See the full description on the dataset page: https://huggingface.co/datasets/Fanoni/medical-ehr-training-data.thinking-data-100-synth
Dataset Card for thinking-data-100
This dataset has been created with distilabel.
Dataset Summary
This dataset contains a pipeline.yaml which can be used to reproduce the pipeline that generated it in distilabel using the distilabel CLI:
distilabel pipeline run --config "https://huggingface.co/datasets/ehristoforu/thinking-data-100/raw/main/pipeline.yaml"
or explore the configuration:
distilabel pipeline info --config… See the full description on the dataset page: https://huggingface.co/datasets/ehristoforu/thinking-data-100-synth.Med-ART_Clinical_Agent_EHR_Dataset
ART — Action-based Reasoning Tasks (Subset)
120-task stratified sample from the ART benchmark introduced in:
ART: Action-based Reasoning Task Benchmarking for Medical AI Agents
Ananya Mantravadi, Shivali Dalmia, Abhishek Mukherji
arXiv:2601.08988
ART is a programmatically generated clinical decision benchmark built on real FHIR patient data. It targets three dominant error categories in medical AI reasoning — retrieval failures, aggregation errors, and conditional logic… See the full description on the dataset page: https://huggingface.co/datasets/CentificAIResearch/Med-ART_Clinical_Agent_EHR_Dataset.