[HTML][HTML] Clinical information extraction applications: a literature review
Background With the rapid adoption of electronic health records (EHRs), it is desirable to
harvest information and knowledge from EHRs to support automated systems at the point of …
harvest information and knowledge from EHRs to support automated systems at the point of …
A review of machine learning and deep learning approaches on mental health diagnosis
Combating mental illnesses such as depression and anxiety has become a global concern.
As a result of the necessity for finding effective ways to battle these problems, machine …
As a result of the necessity for finding effective ways to battle these problems, machine …
Publicly available clinical BERT embeddings
Contextual word embedding models such as ELMo (Peters et al., 2018) and BERT (Devlin et
al., 2018) have dramatically improved performance for many natural language processing …
al., 2018) have dramatically improved performance for many natural language processing …
Natural language processing systems for capturing and standardizing unstructured clinical information: a systematic review
K Kreimeyer, M Foster, A Pandey, N Arya… - Journal of biomedical …, 2017 - Elsevier
We followed a systematic approach based on the Preferred Reporting Items for Systematic
Reviews and Meta-Analyses to identify existing clinical natural language processing (NLP) …
Reviews and Meta-Analyses to identify existing clinical natural language processing (NLP) …
Enhancing clinical concept extraction with contextual embeddings
Objective Neural network–based representations (“embeddings”) have dramatically
advanced natural language processing (NLP) tasks, including clinical NLP tasks such as …
advanced natural language processing (NLP) tasks, including clinical NLP tasks such as …
CLAMP–a toolkit for efficiently building customized clinical natural language processing pipelines
Existing general clinical natural language processing (NLP) systems such as MetaMap and
Clinical Text Analysis and Knowledge Extraction System have been successfully applied to …
Clinical Text Analysis and Knowledge Extraction System have been successfully applied to …
Clinical concept extraction using transformers
Objective The goal of this study is to explore transformer-based models (eg, Bidirectional
Encoder Representations from Transformers [BERT]) for clinical concept extraction and …
Encoder Representations from Transformers [BERT]) for clinical concept extraction and …
Clinical text datasets for medical artificial intelligence and large language models—a systematic review
Privacy and ethical considerations limit access to large-scale clinical datasets, particularly
clinical text data, which contain extensive and diverse information and serve as the …
clinical text data, which contain extensive and diverse information and serve as the …
A survey on recent named entity recognition and relationship extraction techniques on clinical texts
Significant growth in Electronic Health Records (EHR) over the last decade has provided an
abundance of clinical text that is mostly unstructured and untapped. This huge amount of …
abundance of clinical text that is mostly unstructured and untapped. This huge amount of …
Information extraction from electronic medical documents: state of the art and future research directions
MY Landolsi, L Hlaoua, L Ben Romdhane - Knowledge and Information …, 2023 - Springer
In the medical field, a doctor must have a comprehensive knowledge by reading and writing
narrative documents, and he is responsible for every decision he takes for patients …
narrative documents, and he is responsible for every decision he takes for patients …