arXiv:2606.12569v1 Announce Type: new Abstract: We present EDEN (Emergency Department Electronic Notes), a new and unique large-scale corpus of clinical notes produced in Emergency Departments of Italian hospitals. The corpus, in its current version, is composed of approximately 4 million clinical notes fully anonymized, covering diverse phases of patient care during the stay in the emergency department. In addition, a subset of about six thousand notes has been manually annotated by clinical experts through a structured Case Report Form (CRF) containing 132 items relevant for two patient situ
The increasing availability of large-scale, domain-specific datasets is a critical bottleneck for AI development, particularly in non-English languages and specialized fields like healthcare.
This development addresses a significant data scarcity issue for Italian AI research in healthcare, enabling more accurate and contextually relevant models for clinical applications.
The creation of EDEN provides a foundational dataset that will accelerate the development of natural language processing and AI applications for Italian clinical notes, supporting innovation in medical diagnostics and patient care.
- · Italian healthcare AI developers
- · Italian patients
- · NLP researchers
- · Medical informatics companies
- · AI models reliant solely on English data
- · Clinical systems with poor data interoperability
This corpus will directly lead to improved AI models for processing and understanding Italian clinical text, enhancing diagnostic support and administrative efficiency.
Such advancements could enable more personalized medicine approaches in Italy and contribute to harmonized healthcare data standards across Europe.
The success of EDEN might inspire similar large-scale, domain-specific dataset initiatives in other languages and medical specialties, democratizing AI capabilities globally.
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Read at arXiv cs.CL