Search Results for author:
Found 69 papers, 8 papers with code
TL-Explorer: A Digital Humanities Tool for Mapping and Analyzing Translated Literature
TL-Explorer is a digital humanities tool for mapping and analyzing translated literature, encompassing the World Map and the Translation Dashboard.
The Multilingual Anonymisation Toolkit for Public Administrations (MAPA) Project
We describe the MAPA project, funded under the Connecting Europe Facility programme, whose goal is the development of an open-source de-identification toolkit for all official European Union languages.
Re-train or Train from Scratch? Comparing Pre-training Strategies of BERT in the Medical Domain
BERT models used in specialized domains all seem to be the result of a simple strategy: initializing with the original BERT and then resuming pre-training on a specialized corpus.
Cross-lingual Approaches for the Detection of Adverse Drug Reactions in German from a Patient’s Perspective
In this work, we present the first corpus for German Adverse Drug Reaction (ADR) detection in patient-generated content.
Building Comparable Corpora for Assessing Multi-Word Term Alignment
To that aim, we exploit parallel corpora to perform automatic bilingual MWT extraction and comparable corpus construction.
MAPA Project: Ready-to-Go Open-Source Datasets and Deep Learning Technology to Remove Identifying Information from Text Documents
This paper presents the outcomes of the MAPA project, a set of annotated corpora for 24 languages of the European Union and an open-source customisable toolkit able to detect and substitute sensitive information in text documents from any domain, using state-of-the art, deep learning-based named entity recognition techniques.
SEME at SemEval-2024 Task 2: Comparing Masked and Generative Language Models on Natural Language Inference for Clinical Trials
This paper describes our submission to Task 2 of SemEval-2024: Safe Biomedical Natural Language Inference for Clinical Trials.
A Dataset for Pharmacovigilance in German, French, and Japanese: Annotating Adverse Drug Reactions across Languages
User-generated data sources have gained significance in uncovering Adverse Drug Reactions (ADRs), with an increasing number of discussions occurring in the digital world.
Cross-lingual Approaches for the Detection of Adverse Drug Reactions in German from a Patient's Perspective
In this work, we present the first corpus for German Adverse Drug Reaction (ADR) detection in patient-generated content.
Decorate the Examples: A Simple Method of Prompt Design for Biomedical Relation Extraction
In this paper, we investigate prompting for biomedical relation extraction, with experiments on the ChemProt dataset.
Global alignment for relation extraction in Microbiology
We investigate a method to extract relations from texts based on global alignment and syntactic information.
Does constituency analysis enhance domain-specific pre-trained BERT models for relation extraction?
Recently many studies have been conducted on the topic of relation extraction.
C-Norm: a neural approach to few-shot entity normalization
Entity normalization is an important information extraction task which has gained renewed attention in the last decade, particularly in the biomedical and life science domains.
Ranked #1 on
Medical Concept Normalization
on BB-norm-phenotype
CharacterBERT: Reconciling ELMo and BERT for Word-Level Open-Vocabulary Representations From Characters
Due to the compelling improvements brought by BERT, many recent representation models adopted the Transformer architecture as their main building block, consequently inheriting the wordpiece tokenization system despite it not being intrinsically linked to the notion of Transformers.
Ranked #1 on
Semantic Similarity
on ClinicalSTS
Clinical Concept Extraction
Drug–drug Interaction Extraction
+3
Handling Entity Normalization with no Annotated Corpus: Weakly Supervised Methods Based on Distributional Representation and Ontological Information
We propose a new approach to address the scarcity of training data that extends the CONTES method by corpus selection, pre-processing and weak supervision strategies, which can yield high-performance results without any manually annotated examples.
Overview of the Fourth BUCC Shared Task: Bilingual Dictionary Induction from Comparable Corpora
The shared task of the 13th Workshop on Building and Using Comparable Corpora was devoted to the induction of bilingual dictionaries from comparable rather than parallel corpora.
Cross-Lingual Contextual Word Embeddings Mapping With Multi-Sense Words In Mind
Recent work in cross-lingual contextual word embedding learning cannot handle multi-sense words well.
Embedding Strategies for Specialized Domains: Application to Clinical Entity Recognition
Using pre-trained word embeddings in conjunction with Deep Learning models has become the {``}de facto{''} approach in Natural Language Processing (NLP).
Ranked #4 on
Clinical Concept Extraction
on 2010 i2b2/VA
GNEG: Graph-Based Negative Sampling for word2vec
Negative sampling is an important component in word2vec for distributed word representation learning.
Efficient Generation and Processing of Word Co-occurrence Networks Using corpus2graph
Corpus2graph is an open-source NLP-application-oriented tool that generates a word co-occurrence network from a large corpus.
Automatic classification of doctor-patient questions for a virtual patient record query task
We present the work-in-progress of automating the classification of doctor-patient questions in the context of a simulated consultation with a virtual patient.
Representation of complex terms in a vector space structured by an ontology for a normalization task
The method generates continuous vector representations of complex terms in a semantic space structured by the ontology.
zNLP: Identifying Parallel Sentences in Chinese-English Comparable Corpora
This paper describes the zNLP system for the BUCC 2017 shared task.
Overview of the Second BUCC Shared Task: Spotting Parallel Sentences in Comparable Corpora
We examined manually a small sample of the false negative sentence pairs for the most precise French-English runs and estimated the number of parallel sentence pairs not yet in the provided gold standard.
Traitement automatique de la langue biom\'edicale au LIMSI (Biomedical language processing at LIMSI)
Nous proposons des d{\'e}monstrations de trois outils d{\'e}velopp{\'e}s par le LIMSI en traitement automatique des langues appliqu{\'e} au domaine biom{\'e}dical : la d{\'e}tection de concepts m{\'e}dicaux dans des textes courts, la cat{\'e}gorisation d{'}articles scientifiques pour l{'}assistance {\`a} l{'}{\'e}criture de revues syst{\'e}matiques, et l{'}anonymisation de textes cliniques.
Tri Automatique de la Litt\'erature pour les Revues Syst\'ematiques (Automatically Ranking the Literature in Support of Systematic Reviews)
Nous appliquons un mod{\`e}le de regression logistique sur deux corpus issus de revues syst{\'e}matiques conduites dans le domaine du traitement automatique de la langue et de l{'}efficacit{\'e} des m{\'e}dicaments.
D\'etection de concepts et granularit\'e de l'annotation (Concept detection and annotation granularity )
Nous faisons l{'}hypoth{\`e}se qu{'}une annotation {\`a} un niveau de granularit{\'e} plus fin, typiquement au niveau de l{'}{\'e}nonc{\'e}, devrait am{\'e}liorer la performance d{'}un d{\'e}tecteur automatique entra{\^\i}n{\'e} sur ces donn{\'e}es.
Supervised classification of end-of-lines in clinical text with no manual annotation
In some plain text documents, end-of-line marks may or may not mark the boundary of a text unit (e. g., of a paragraph).
Detection of Text Reuse in French Medical Corpora
Electronic Health Records (EHRs) are increasingly available in modern health care institutions either through the direct creation of electronic documents in hospitals{'} health information systems, or through the digitization of historical paper records.
A Dataset for ICD-10 Coding of Death Certificates: Creation and Usage
Very few datasets have been released for the evaluation of diagnosis coding with the International Classification of Diseases, and only one so far in a language other than English.
Impact de l'agglutination dans l'extraction de termes en arabe standard moderne (Adaptation of a term extractor to the Modern Standard Arabic language)
L{'}adaptation a d{'}abord consist{\'e} {\`a} d{\'e}crire le processus d{'}extraction des termes de mani{\`e}re similaire {\`a} celui d{\'e}fini pour l{'}anglais et le fran{\c{c}}ais en prenant en compte certains particularit{\'e}s morpho-syntaxiques de la langue arabe.
Une cat\'egorisation de fins de lignes non-supervis\'ee (End-of-line classification with no supervision)
Nous proposons une m{\'e}thode enti{\`e}rement non-supervis{\'e}e pour d{\'e}terminer si une fin de ligne doit {\^e}tre vue comme un simple espace ou comme une v{\'e}ritable fronti{\`e}re d{'}unit{\'e} textuelle, et la testons sur un corpus de comptes rendus m{\'e}dicaux.
Managing Linguistic and Terminological Variation in a Medical Dialogue System
We introduce a dialogue task between a virtual patient and a doctor where the dialogue system, playing the patient part in a simulated consultation, must reconcile a specialized level, to understand what the doctor says, and a lay level, to output realistic patient-language utterances.
Identification of Drug-Related Medical Conditions in Social Media
When trained on the output of the first classifier, the second classifier{'}s performances are the following: p=0. 683;r=0. 956;f1=0. 797.
Transfer-Based Learning-to-Rank Assessment of Medical Term Technicality
While measuring the readability of texts has been a long-standing research topic, assessing the technicality of terms has only been addressed more recently and mostly for the English language.
\'Etude des verbes introducteurs de noms de m\'edicaments dans les forums de sant\'e
Nous estimons que l{'}analyse de ces variantes pourrait permettre de mod{\'e}liser les erreurs faites par les usagers des forums lorsqu{'}ils {\'e}crivent les noms de m{\'e}dicaments, et am{\'e}liorer en cons{\'e}quence les syst{\`e}mes de recherche d{'}information.
Un patient virtuel dialogant
Le d{\'e}monstrateur que nous d{\'e}crivons ici est un prototype de syst{\`e}me de dialogue dont l{'}objectif est de simuler un patient.
M\'edicaments qui soignent, m\'edicaments qui rendent malades : \'etude des relations causales pour identifier les effets secondaires
Dans cet article, nous nous int{\'e}ressons {\`a} la mani{\`e}re dont sont exprim{\'e}s les liens qui existent entre un traitement m{\'e}dical et un effet secondaire.
Identification de facteurs de risque pour des patients diab\'etiques \`a partir de comptes-rendus cliniques par des approches hybrides
Dans cet article, nous pr{\'e}sentons les m{\'e}thodes que nous avons d{\'e}velopp{\'e}es pour analyser des comptes- rendus hospitaliers r{\'e}dig{\'e}s en anglais.
Use of unsupervised word classes for entity recognition: Application to the detection of disorders in clinical reports
We design and test two syntax-based methods to produce word classes: one applies the Brown clustering algorithm to syntactic dependencies, the other collects latent categories created by a PCFG-LA parser.
Annotation of specialized corpora using a comprehensive entity and relation scheme
We present the annotation scheme as well as the results of a pilot annotation study covering 35 clinical documents in a variety of subfields and genres.
Language Resources for French in the Biomedical Domain
The biomedical domain offers a wealth of linguistic resources for Natural Language Processing, including terminologies and corpora.
The Quaero French Medical Corpus: A Ressource for Medical Entity Recognition and Normalization
Overall, a total of 26, 409 entity annotations were mapped to 5, 797 unique UMLS concepts.
Extended Named Entities Annotation on OCRed Documents: From Corpus Constitution to Evaluation Campaign
Within the framework of the Quaero project, we proposed a new definition of named entities, based upon an extension of the coverage of named entities as well as the structure of those named entities.
Named Entity Recognition (NER)
Optical Character Recognition (OCR)
Identifying bilingual Multi-Word Expressions for Statistical Machine Translation
MultiWord Expressions (MWEs) repesent a key issue for numerous applications in Natural Language Processing (NLP) especially for Machine Translation (MT).
