8 papers
AAbAAC: An Annotated Corpus for Autoimmunity Information Extraction
Fabien Maury, Solène Grosdidier, Maud de Dieuleveult +1
Despite advances in information extraction driven by deep learning and large language models, performance gaps remain in highly specialized biomedical fields, where domainspecific…
Shapley Regression for Rare Disease Diagnosis Support: a case study on APDS
Safa Alsaidi, Tomás Brogueira, Nizar Mahlaoui +5
Activated PI3K8 Syndrome (APDS) is a rare genetic immune disorder caused by variants in PIK3CD or PIK3R1, with highly heterogeneous symptoms that often delay diagnosis. Early recog…
Analysing Lightweight Large Language Models for Biomedical Named Entity Recognition on Diverse Ouput Formats
Pierre Epron, Adrien Coulet, Mehwish Alam
Despite their strong linguistic capabilities, Large Language Models (LLMs) are computationally demanding and require substantial resources for fine-tuning, which is unadapted to pr…
Clinical Data Goes MEDS? Let's OWL make sense of it
Alberto Marfoglia, Jong Ho Jhee, Adrien Coulet
The application of machine learning on healthcare data is often hindered by the lack of standardized and semantically explicit representation, leading to limited interoperability a…
Predicting clinical outcomes from patient care pathways represented with temporal knowledge graphs
Jong Ho Jhee, Alberto Megina, Pacôme Constant Dit Beaufils +4
Background: With the increasing availability of healthcare data, predictive modeling finds many applications in the biomedical domain, such as the evaluation of the level of risk f…
Comparing representations of long clinical texts for the task of patient note-identification
Safa Alsaidi, Marc Vincent, Olivia Boyer +3
In this paper, we address the challenge of patient-note identification, which involves accurately matching an anonymized clinical note to its corresponding patient, represented by…