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Unlocking rare cancer data: using large language models to extract information from clinical notes
One of the main objectives of the IDEA4RC project is to develop an algorithm capable of extracting data from clinicians’ notes and pathology or radiology reports stored within the hospital’s information system. Currently, a wealth of information is locked within these texts, which cannot be fully utilized by researchers to uncover more about rare cancers,…
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IDEA4RC at MIE24
IDEA4RC members participated in the 34th Medical InformaticsEurope Conference (MIE 24) that was held in Athens from August 25th to 29th. The theme of the congress was “Digital Health and Informatics Innovations for Sustainable Health Care Systems”. On August 27th, IDEA4RC partners held the workshop “Towards a European Cancer Minimum Data Model and European Oncology…
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An open-source multilingual LLM for the medical domain
I. García-Ferrero, et al, “MedMT5: An Open-Source Multilingual Text-to-Text LLM for the Medical Domain”, Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024). Full text available here. Abstract Research on language technology for the development of medical applications is currently a hot topic in Natural Language Understanding and…
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Latest highlights in medical NLP across multiple languages
This survey aims to provide an overview of the current state of biomedical and clinical Natural Language Processing research and practice in Languages other than English.
Intelligent ecosystem to improve
the governance, the sharing,
and the re-use of health data for rare cancers