Recent advances in biomedical literature mining
The recent years have witnessed a rapid increase in the number of scientific articles in
biomedical domain. These literature are mostly available and readily accessible in …
biomedical domain. These literature are mostly available and readily accessible in …
[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 …
mine knowledge from unstructured health-related texts. Recent advances in noisy text …
[HTML][HTML] Fine-tuning bidirectional encoder representations from transformers (BERT)–based models on large-scale electronic health record notes: an empirical study
Background: The bidirectional encoder representations from transformers (BERT) model has
achieved great success in many natural language processing (NLP) tasks, such as named …
achieved great success in many natural language processing (NLP) tasks, such as named …
[HTML][HTML] A simple neural vector space model for medical concept normalization using concept embeddings
Objective Medical concept normalization (MCN), the task of linking textual mentions to
concepts in an ontology, provides a solution to unify different ways of referring to the same …
concepts in an ontology, provides a solution to unify different ways of referring to the same …
Knowledge-graph-enabled biomedical entity linking: a survey
Abstract Biomedical Entity Linking (BM-EL) task, which aims to match biomedical mentions
in articles to entities in a certain knowledge base (eg, the Unified Medical Language …
in articles to entities in a certain knowledge base (eg, the Unified Medical Language …
The 2019 National Natural language processing (NLP) Clinical Challenges (n2c2)/Open Health NLP (OHNLP) shared task on clinical concept normalization for …
Objective The 2019 National Natural language processing (NLP) Clinical Challenges
(n2c2)/Open Health NLP (OHNLP) shared task track 3, focused on medical concept …
(n2c2)/Open Health NLP (OHNLP) shared task track 3, focused on medical concept …
A transition-based joint model for disease named entity recognition and normalization
Motivation Disease named entities play a central role in many areas of biomedical research,
and automatic recognition and normalization of such entities have received increasing …
and automatic recognition and normalization of such entities have received increasing …
The 2019 n2c2/UMass Lowell shared task on clinical concept normalization
Abstract Objective The n2c2/UMass Lowell spin-off shared task focused on medical concept
normalization (MCN) in clinical records. This task aimed to assess state-of-the-art methods …
normalization (MCN) in clinical records. This task aimed to assess state-of-the-art methods …
Unified Medical Language System resources improve sieve-based generation and Bidirectional Encoder Representations from Transformers (BERT)–based ranking …
Objective Concept normalization, the task of linking phrases in text to concepts in an
ontology, is useful for many downstream tasks including relation extraction, information …
ontology, is useful for many downstream tasks including relation extraction, information …
[HTML][HTML] Automatic full conversion of clinical terms into SNOMED CT concepts
RJ Kate - Journal of Biomedical Informatics, 2020 - Elsevier
SNOMED CT is the most comprehensive clinical ontology and is also amenable for
automated reasoning. However, in order to unleash its full potential for automated reasoning …
automated reasoning. However, in order to unleash its full potential for automated reasoning …