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Found 4 papers, 0 papers with code
Classification multilabel de concepts médicaux pour l’identification du profil clinique du patient (Multilabel classification of medical concepts for patient’s clinical profile identification )
Nous avons également proposé un modèle « bout-enbout », avec une première phase d’extraction d’entités nommées également basée sur un transformer de type camembert-large et un classifieur de genre sur un modèle Adaboost.
Impact of translation on biomedical information extraction from real-life clinical notes
The objective of our study is to determine whether using English tools to extract and normalize French medical concepts on translations provides comparable performance to French models trained on a set of annotated French clinical notes.
Detecting automatically the layout of clinical documents to enhance the performances of downstream natural language processing
The precision, recall, and F1 score per document for the acute infection detection algorithm were 82. 54 (95CI 72. 86-91. 60), 85. 24 (95CI 76. 61-93. 70), 83. 87 (95CI 76, 92-90. 08) with exploitation of the results of the advanced body extraction algorithm, respectively.
Development and validation of a natural language processing algorithm to pseudonymize documents in the context of a clinical data warehouse
The objective of this study is to address the critical issue of de-identification of clinical reports in order to allow access to data for research purposes, while ensuring patient privacy.
