Visualization of medical concepts represented using word embeddings: a scoping review
N Oubenali, S Messaoud, A Filiot, A Lamer… - BMC medical informatics …, 2022 - Springer
Background Analyzing the unstructured textual data contained in electronic health records
(EHRs) has always been a challenging task. Word embedding methods have become an …
(EHRs) has always been a challenging task. Word embedding methods have become an …
[HTML][HTML] Applying Natural Language Processing to Textual Data From Clinical Data Warehouses: Systematic Review
Background In recent years, health data collected during the clinical care process have
been often repurposed for secondary use through clinical data warehouses (CDWs), which …
been often repurposed for secondary use through clinical data warehouses (CDWs), which …
Identifying multi-resolution clusters of diseases in ten million patients with multimorbidity in primary care in England
Background Identifying clusters of diseases may aid understanding of shared aetiology,
management of co-morbidities, and the discovery of new disease associations. Our study …
management of co-morbidities, and the discovery of new disease associations. Our study …
Detecting of a patient's condition from clinical narratives using natural language representation
The rapid progress in clinical data management systems and artificial intelligence
approaches enable the era of personalized medicine. Intensive care units (ICUs) are ideal …
approaches enable the era of personalized medicine. Intensive care units (ICUs) are ideal …
AliBERT: A pretrained language model for French biomedical text
A Berhe, G Draznieks, V Martenot, V Masdeu, L Davy… - 2023 - hal.science
Over the past few years, domain specific pretrained language models have been
investigated and have shown remarkable achievements in different downstream tasks …
investigated and have shown remarkable achievements in different downstream tasks …
Comparing neural language models for medical concept representation and patient trajectory prediction
Effective representation of medical concepts is crucial for secondary analyses of electronic
health records. Neural language models have shown promise in automatically deriving …
health records. Neural language models have shown promise in automatically deriving …
Computational thematics: comparing algorithms for clustering the genres of literary fiction
What are the best methods of capturing thematic similarity between literary texts? Knowing
the answer to this question would be useful for automatic clustering of book genres, or any …
the answer to this question would be useful for automatic clustering of book genres, or any …
[HTML][HTML] Boosting biomedical document classification through the use of domain entity recognizers and semantic ontologies for document representation: The case of …
The increasing number of scientific research documents published keeps growing at an
unprecedented rate, making it increasingly difficult to access practical information within a …
unprecedented rate, making it increasingly difficult to access practical information within a …
[HTML][HTML] Semantic deep learning: Prior knowledge and a type of four-term embedding analogy to acquire treatments for well-known diseases
Background: How to treat a disease remains to be the most common type of clinical
question. Obtaining evidence-based answers from biomedical literature is difficult …
question. Obtaining evidence-based answers from biomedical literature is difficult …
[HTML][HTML] Discovering the context of people with disabilities: Semantic categorization test and environmental factors mapping of word embeddings from Reddit
Background: The World Health Organization's International Classification of Functioning
Disability and Health (ICF) conceptualizes disability not solely as a problem that resides in …
Disability and Health (ICF) conceptualizes disability not solely as a problem that resides in …