Papers by Nicolas Hiebel
“Women do not have heart attacks!” Gender Biases in Automatically Generated Clinical Cases in French (2025.findings-naacl)
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| Challenge: | Healthcare professionals are increasingly including Language Models (LMs) in clinical practice. |
| Approach: | They propose to use LMs to generate clinical cases in french and an automatic linguistic gender detection tool to measure gender biases. |
| Outcome: | The proposed model over-generates cases describing male patients, creating synthetic corpora that are not consistent with documented prevalence for these disorders. |
Can Synthetic Text Help Clinical Named Entity Recognition? A Study of Electronic Health Records in French (2023.eacl-main)
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| Challenge: | In sensitive domains, the sharing of corpora is restricted due to confidentiality, copyrights or trade secrets. |
| Approach: | They use auto-regressive neural models to generate a clinical case corpus annotated with clinical entities and evaluate it for a named entity recognition task. |
| Outcome: | The proposed model can produce clinical case corpus annotated with clinical entities while maintaining confidentiality. |
CLISTER : A Corpus for Semantic Textual Similarity in French Clinical Narratives (2022.lrec-1)
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| Challenge: | Modern Natural Language Processing relies on the availability of annotated corpora for training and evaluation. |
| Approach: | They propose to annotate sentences in French using a definition of similarity guided by clinical facts and use it to evaluate the corpus. |
| Outcome: | The proposed model can capture similarity with state-of-the-art performance on the DEFT STS shared task evaluation data set. |