EDEN: New Large-Scale Italian Clinical Notes Dataset Released for Medical AI Research
Researchers have released EDEN, a corpus of approximately 4 million anonymized clinical notes from Italian emergency departments, with 6,000 notes manually annotated by medical experts. The dataset addresses a significant gap in available medical data for the Italian language and is designed to support development of Large Language Models in clinical applications. This resource is notable as the largest freely available clinical notes corpus for Italian and introduces a structured information extraction benchmark for emergency medicine scenarios.
EDEN (Emergency Department Electronic Notes) is a newly published dataset comprising roughly 4 million fully anonymized clinical notes from Italian hospital emergency departments, covering various phases of patient care. A subset of approximately 6,000 notes has been manually annotated by clinical experts using a structured Case Report Form containing 132 items relevant to two emergency scenarios: dyspnea and loss of consciousness. The annotation items capture diverse data types including numerical values (e.g., blood saturation), categorical values (e.g., consciousness level), binary indicators (e.g., trauma presence), and mixed types. The annotation process involved multiple clinicians with iterative revision to resolve ambiguities. The researchers propose CRF-filling as a novel structured information extraction benchmark and provide baseline results using Gemma-27B and MedGemma-27B models. According to the authors, EDEN is the largest freely available corpus of clinical notes for the Italian language.
What's missing
The dataset's limitations and imbalances are mentioned (described as 'high imbalanced') but specific details about class distribution, potential biases in the source population, data quality metrics, inter-annotator agreement scores, and plans for public access/licensing are not provided in the abstract.
What different sources said
- arXiv cs.AICenter
EDEN: A Large-Scale Corpus of Clinical Notes for Italian
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