Clinical natural language processing in languages other than English: opportunities and challenges

A Névéol, H Dalianis, S Velupillai, G Savova… - Journal of biomedical …, 2018 - Springer
Background Natural language processing applied to clinical text or aimed at a clinical
outcome has been thriving in recent years. This paper offers the first broad overview of …

An overview of biomedical entity linking throughout the years

E French, BT McInnes - Journal of biomedical informatics, 2023 - Elsevier
Abstract Biomedical Entity Linking (BEL) is the task of map** of spans of text within
biomedical documents to normalized, unique identifiers within an ontology. This is an …

DrBERT: A robust pre-trained model in French for biomedical and clinical domains

Y Labrak, A Bazoge, R Dufour, M Rouvier… - arxiv preprint arxiv …, 2023 - arxiv.org
In recent years, pre-trained language models (PLMs) achieve the best performance on a
wide range of natural language processing (NLP) tasks. While the first models were trained …

Evaluating the carbon footprint of NLP methods: a survey and analysis of existing tools

N Bannour, S Ghannay, A Névéol… - Proceedings of the …, 2021 - aclanthology.org
Abstract Modern Natural Language Processing (NLP) makes intensive use of deep learning
methods because of the accuracy they offer for a variety of applications. Due to the …

[HTML][HTML] A clinician friendly data warehouse oriented toward narrative reports: Dr. Warehouse

N Garcelon, A Neuraz, R Salomon, H Faour… - Journal of biomedical …, 2018 - Elsevier
Introduction Clinical data warehouses are often oriented toward integration and exploration
of coded data. However narrative reports are of crucial importance for translational research …

[HTML][HTML] Capturing the patient's perspective: a review of advances in natural language processing of health-related text

G Gonzalez-Hernandez, A Sarker… - Yearbook of medical …, 2017 - thieme-connect.com
Background: Natural Language Processing (NLP) methods are increasingly being utilized to
mine knowledge from unstructured health-related texts. Recent advances in noisy text …

Overview of the CLEF eHealth evaluation lab 2019

L Kelly, H Suominen, L Goeuriot, M Neves… - Experimental IR Meets …, 2019 - Springer
In this paper, we provide an overview of the seventh annual edition of the CLEF eHealth
evaluation lab. CLEF eHealth 2019 continues our evaluation resource building efforts …

Extracting symptoms and their status from clinical conversations

N Du, K Chen, A Kannan, L Tran, Y Chen… - arxiv preprint arxiv …, 2019 - arxiv.org
This paper describes novel models tailored for a new application, that of extracting the
symptoms mentioned in clinical conversations along with their status. Lack of any publicly …

MT-clinical BERT: scaling clinical information extraction with multitask learning

A Mulyar, O Uzuner, B McInnes - Journal of the American …, 2021 - academic.oup.com
Objective Clinical notes contain an abundance of important, but not-readily accessible,
information about patients. Systems that automatically extract this information rely on large …

Overview of the CLEF eHealth evaluation lab 2015

L Goeuriot, L Kelly, H Suominen, L Hanlen… - Experimental IR Meets …, 2015 - Springer
This paper reports on the 3rd CLEFeHealth evaluation lab, which continues our evaluation
resource building activities for the medical domain. In this edition of the lab, we focus on …