Deep learning in clinical natural language processing: a methodical review
Objective This article methodically reviews the literature on deep learning (DL) for natural
language processing (NLP) in the clinical domain, providing quantitative analysis to answer …
language processing (NLP) in the clinical domain, providing quantitative analysis to answer …
What does it mean for a language model to preserve privacy?
Natural language reflects our private lives and identities, making its privacy concerns as
broad as those of real life. Language models lack the ability to understand the context and …
broad as those of real life. Language models lack the ability to understand the context and …
Evaluating the carbon footprint of NLP methods: a survey and analysis of existing tools
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 …
methods because of the accuracy they offer for a variety of applications. Due to the …
[HTML][HTML] Early stopping by correlating online indicators in neural networks
In order to minimize the generalization error in neural networks, a novel technique to identify
overfitting phenomena when training the learner is formally introduced. This enables support …
overfitting phenomena when training the learner is formally introduced. This enables support …
A clinical trials corpus annotated with UMLS entities to enhance the access to evidence-based medicine
L Campillos-Llanos, A Valverde-Mateos… - BMC medical informatics …, 2021 - Springer
Background The large volume of medical literature makes it difficult for healthcare
professionals to keep abreast of the latest studies that support Evidence-Based Medicine …
professionals to keep abreast of the latest studies that support Evidence-Based Medicine …
[HTML][HTML] Medical concept normalization in French using multilingual terminologies and contextual embeddings
P Wajsbürt, A Sarfati, X Tannier - Journal of Biomedical Informatics, 2021 - Elsevier
Introduction Concept normalization is the task of linking terms from textual medical
documents to their concept in terminologies such as the UMLS®. Traditional approaches to …
documents to their concept in terminologies such as the UMLS®. Traditional approaches to …
[HTML][HTML] Supervised methods to extract clinical events from cardiology reports in Italian
Clinical narratives are a valuable source of information for both patient care and biomedical
research. Given the unstructured nature of medical reports, specific automatic techniques …
research. Given the unstructured nature of medical reports, specific automatic techniques …
Extracting umls concepts from medical text using general and domain-specific deep learning models
Entity recognition is a critical first step to a number of clinical NLP applications, such as entity
linking and relation extraction. We present the first attempt to apply state-of-the-art entity …
linking and relation extraction. We present the first attempt to apply state-of-the-art entity …
Closing the gap: Joint de-identification and concept extraction in the clinical domain
Exploiting natural language processing in the clinical domain requires de-identification, ie,
anonymization of personal information in texts. However, current research considers de …
anonymization of personal information in texts. However, current research considers de …
Extracting clinical event timelines: temporal information extraction and coreference resolution in electronic health records
J Tourille - 2018 - theses.hal.science
Important information for public health is contained within Electronic Health Records (EHRs).
The vast majority of clinical data available in these records takes the form of narratives …
The vast majority of clinical data available in these records takes the form of narratives …